2022

  1. Qinhu Zhang, Ying He, Siguo Wang, Zhanheng Chen, Zhenhao Guo, Zhen Cui, Qi Liu, and D.S.Huang, "Base-resolution prediction of transcription factor binding signals by a deep learning framework," PLOS Computational Biology, 2022, 18(3): e1009941.
  2. Zhen Shen, Qinhu Zhang, Kyungsook Han, D.S.Huang, "A deep learning model for RNA-protein binding preference prediction based on hierarchical LSTM and attention network," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19(2): 753-762, 2022.
  3. Jianbing Huang, D.S.Huang,"Deep reinforcement learning based trajectory pricing on ride-hailing platforms," ACM Transactions on Intelligent Systems and Technology, Vol.13, No.3, Article 41, 2022.

2021

  1. Yu Zheng, Yifeng Sun, Yue Kuai, Guoxiang Fu, Huimin An, Jinyun Chen, Jiajun Zhu, Yixin Wo, Yiwang Wu, Kaibin Song, Qinghua Xu, Di Wu, D.S.Huang, Qifeng Wang, Hongming Pan, "Gene expression profiling for the diagnosis of multiple primary malignant tumors", Cancer Cell International, Vol. 21, No. 1: 1-9, January 2021.
  2. Qifeng Wang, Linyi Hu, Wenyong Ma, Zhipeng Meng, Peng Li, Xiao Zhang, Yingjia Wang, Yangyang Lu, Yifeng Sun, Yiwang Wu, Wanli Ren, Kaibin Song, Jinying Chen, Sheng Wu, Qinghua Xu, D.S.Huang, Dahong Zhang, Yijun Shen, Dingwei Ye, "UriBLAD: A Urine-Based Gene Expression Assay for Noninvasive Detection of Bladder Cancer", The Journal of Molecular Diagnostics, Vol. 23, No. 1: 61-70, January 2021.
  3. Zhen-Hao Guo, Zhu-Hong You, D.S.Huang, Hai-Cheng Yi, Kai Zheng, Zhan-Heng Chen, Yan-Bin Wang,"MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm," Briefings in Bioinformatics, 2021, 22(2): 2085-2095.
  4. Yong Wu, Kun Zhang, Di Wu, Chao Wang, Chang-An Yuan, Xiao Qin, Tao Zhu, Yu-Chuan Du, Han-Li Wang, D.S.Huang, " Person reidentification by multiscale feature representation learning with random batch feature mask," IEEE Transactions on Cognitive and Developmental Systems, 13(4): 865-874, 2021.
  5. Hai-Cheng Yi, Zhu-Hong You, Zhen-Hao Guo, D.S.Huang, Keith C.C. Chan, "Learning Representation of Molecules in Association Network for Predicting Intermolecular Associations," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18(6): 2546-2554, 2021.
  6. Saud Alguwaizania, Shulei Rena, D.S.Huang, Kyungsook Han, "Predicting interactions between pathogen and human proteins based on the relation between sequence length and amino acid composition," Current Bioinformatics, 16(6): 799-806, 2021 (DOI: 10.2174/1574893616666210430133846).
  7. Qinhu Zhang, Dailun Wang, Kyungsook Han, and D.S.Huang, "Predicting TF-DNA binding motifs from ChIP-seq datasets using the bag-based classifier combined with a multi-fold learning scheme," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18(5): 1743-1751, 2021
  8. Qinhu Zhang, Wenbo Yu, Kyungsook Han, Asoke K. Nandi, and D.S.Huang, "Multi-scale capsule network for predicting DNA-protein binding sites," IEEE-ACM Transactions on Computational Biology and Bioinformatics,18(5): 1793-1800, 2021.
  9. Qinhu Zhang, Siguo Wang, Zhanheng Chen, Ying He, Qi Liu, D.S.Huang, " Locating transcription factor binding sites by fully convolutional neural network," Briefings in Bioinformatics, 22(5): bbaa435, 2021.
  10. Ying He, Zhen Shen, Qinhu Zhang, Siguo Wang, D.S.Huang, " A survey on Deep Learning in DNA/RNA motif mining," Briefings in Bioinformatics, 22(4): bbaa229, 2021
  11. Qinhu Zhang, Zhen Shen and D.S.Huang, "Predicting in-vitro transcription factor binding sites using DNA sequence + shape," IEEE/ACM Transactions on Computational Biology and Bioinformatics,18(2): 667-676, 2021.
  12. Siguo Wang, Qinhu Zhang, Zhen Shen, Ying He, Zhen-Heng Chen, Jianqiang Li, and D.S.Huang, "Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture," Molecular Therapy - Nucleic Acids, vol. 24, pp. 154-163, 2021.
  13. Di Wu, Chao Wang, Yong Wu, Qi-Cong Wang and D.S.Huang, "Attention deep model with multi-scale deep supervision for person re-identification," IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 5, no. 1, pp. 70-78. 2021.
  14. Van-Thanh Hoang, D.S.Huang and Kang-Hyun Jo, "3-D Facial Landmarks Detection for Intelligent Video Systems," IEEE Transactions on Industrial Informatics, vol. 17, no. 1, pp. 578-586, Jan. 2021.

 

2020

  1. Zhen Shen, Suping Deng, D.S.Huang,“RNA-Protein binding sites prediction via multi- scale convolutional gated recurrent unit networks,” IEEE Transactions on Computational Biology and Bioinformatics, vol.17, no.5: 1741-1750, 2020.
  2. Chen Peng，Yang Zheng, and D.S.Huang, "Capsule network based modeling of multi-omics data for discovery of breast cancer-related genes," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.17, no.5: 1605-1612, 2020.
  3. Zhen Shen, Su-Ping Deng, D.S.Huang, "Capsule network for predicting RNA-Protein binding preferences using hybrid feature," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.17, no.5: 1483-1492, 2020.
  4. Wook Lee, D.S.Huang, Kyungsook Han, “Constructing cancer patient-specific and group-specific gene networks with multi-omics data,” BMC Medical Genomics, vol.13, SI.6, 2020.
  5. Hai-Cheng Yi, Zhu-Hong You, D.S.Huang, Zhen-Hao Guo, Keith C.C. Chan, YM Li, “Learning representations to predict intermolecular interactions on large-scale heterogeneous molecular association network,” ISCIENCE, vol.23, no.7, 2020, DOI: 10.1016/j.isci.2020.101261.
  6. Lei Wang, Zhu-Hong You, Yu-An Huang, D.S.Huang, Keith Chan, “An efficient approach based on multi-sources information to predict circRNA-disease associations using deep convolutional neural network,”Bioinformatics, vol.36, no.13: 4038-4046, 2020.
  7. Zhen-Hao Guo, Zhu-Hong You, D.S.Huang, Hai-Cheng Yi, Zhan-Heng Chen, Yan-Bin Wang, “A learning based framework for diverse biomolecule relationship prediction in molecular association network,” Communications Biology, no.3: 118, 2020 (https://doi.org/10.1038/s42003-020-0858-8).
  8. Qing Ye, Qifeng Wang, Peng Qi, Jinying Chen, Yifeng Sun, Shichai Jin, Wanli Ren, Chengshu Chen,Mei Liu, Midie Xu, Gang Ji, Jun Yang, Ling Nie, Qinghua Xu, D.S.Huang, Xiang Du, and Xiaoyan Zhou, "Development and Clinical Validation of a 90-Gene Expression Assay for Identifying Tumor Tissue Origin", The Journal of Molecular Diagnostics, Vol. 22, No. 9: 1139-1150, September 2020.
  9. Lei Wang, Zhu-Hong You, D.S.Huang, Fengfeng Zhou, “Combining high speed ELM learning with a deep convolutional neural network feature encoding for predicting protein-RNA interactions,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.17, no.3: 972-980, 2020.
  10. Qinhu Zhang, Lin Zhu, Wenzheng Bao, D.S.Huang, "Weakly-supervised convolutional neural network architecture for predicting protein-DNA binding," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.17, no.2: 679-689, 2020.
  11. Wenzheng Bao, D.S.Huang, Yuehui Chen, “MSIT: Malonylation Sites Identification Tree”, Current Bioinformatics, vol.15, no.1: 59-67, 2020.

 

2019

  1. Xianpeng Liang, Di Wu, D.S.Huang, "Image co-segmentation via locally biased discriminative clustering," IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 11: 2228-2233, Nov. 2019.
  2. Di Wu, Si-Jia Zheng, Xiao-Ping Zhang, Chang-An Yuan, Fei Cheng, Yang Zhao, Yong-Jun Lin, Zhong-Qiu Zhao, Yong-Li Jiang and D.S.Huang, "Deep learning based methods for person re-identification: A comprehensive review," Neurocomputing,vol.337: 354-371, 2019.
  3. Di Wu, Kun Zhang, Si-Jia Zheng, Yong-Tao Hao, Fu-Qiang Liu, Xiao Qin, Fei Cheng, Yang Zhao, Qi Liu, Chang-An Yuan and D.S.Huang, “Random occlusion-recovery for person re-identification,” Journal of Imaging Science & Technology, 63(3), pp. 30405-1-30405-9(9), 2019.
  4. Qinhu Zhang, Lin Zhu, and D.S.Huang,"High-order convolutional neural network architecture for predicting DNA-protein binding sites", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.16, no.4: 1184-1192, 2019.
  5. Qinhu Zhang, Zhen Shen, De-Shuang Huang, "Modeling in-vivo protein-DNA binding by combining multiple-instance learning with a hybrid deep neural network," Scientific Reports, 9: 8484, 2019.
  6. Lin Yuan, D.S.Huang, “A network-guided association mapping approach from DNA methylation to disease,” Scientific Reports, 9: 5601, 2019.
  7. Lin Yuan, Le-Hang Guo, Chang-An Yuan, You-Hua Zhang, Kyungsook Han, Asoke K. Nandi, Barry Honig, and De-Shuang Huang, “Integration of multi-omics data for gene regulatory network inference and application to breast cancer,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16, no.3: 782-791, 2019.
  8. Wenzheng Bao, Bin Yang, D.S.Huang, Dong Wang, Yue-Hui Chen, Qi Liu, Rong Bao, “IMKPse: Identification of Protein Malonylation Sites by the Key Features into General PseAAC,” IEEE Access, 7(1): pp.54073-54083, Dec., 2019.
  9. Wenxuan Xu, Lin Zhu and D.S.Huang, "DCDE: An efficient deep convolutional divergence encoding method for human promoter recognition," IEEE Transactions on NanoBioscience, vol.18, no.2: 136-145, 2019.
  10. Li, Z.T. Fan, X.L. Zhang, and D.S.Huang, “Robust dimensionality reduction via feature space to feature space distance metric learning,” Neural Networks, 112(4): 1-14, 2019.
  11. Di Wu, Hong-Wei Yang, D.S.Huang, Chang-An Yuan, Xiao Qin, Yang Zhao, Xin-Yong Zhao, Jian-Hong Sun. "Omnidirectional feature learning for person re-identification," IEEE Access, vol. 7, pp. 28402-28411, 2019.
  12. Di Wu, Si-Jia Zheng, Chang-An Yuan and D.S.Huang, "A deep model with combined losses for person re-identification." Cognitive Systems Research, 54: 74-82, 2019.
  13. Di Wu, Si-Jia Zheng, Wen-Zheng Bao, Xiao-Ping Zhang, Chang-An Yuan and D.S.Huang,"A novel deep model with multi-loss and efficient training for person re-identification," Neurocomputing, 324, pp. 69-76, 2019.
  14. Feng Zou, Debao Chen, D.S.Huang, Renquan Lu, Xude Wang, “Inverse modelling-based multi-objective evolutionary algorithm with decomposition for community detection in complex networks”Physica A-Statistical Mechanics and Its Applications, 513 :662-674,2019.

 

2018

  1. Chen Peng, Liang Zou, D.S.Huang, "Discovery of relationships between long non-coding RNAs and genes in human diseases based on tensor completion," IEEE Access, vol. 6, pp. 59152-59162, 2018.
  2. Bin Yang, Wenzheng Bao, D.S.Huang, and Yuehui Chen, "Inference of large-scale time-delayed gene regulatory network with parallel mapReduce cloud platform," Scientific Reports, 8: 17787, 2018.
  3. Zhen Shen, Wen-Zheng Bao, D.S.Huang, “Recurrent neural network for predicting transcription factor binding sites,” Scientific Reports, 8: 15270, 2018.
  4. Bin Liu, Fan Weng, D.S.Huang, Kuo-Chen Chou, "HSCVFNT: Inference of time-delayed gene regulatory network based on complex-valued flexible neural tree model," International Journal of Molecular Sciences,19(10): 3178, 2018.
  5. Hongbo Zhang, Lin Zhu, D.S.Huang,"DiscMLA: An efficient discriminative motif learning algorithm over high-throughput datasets," IEEE/ACM Transactions on Computational Biology and Bioinformatics,15(6):1810-1820, 2018.
  6. Bin Liu, Fan Weng, D.S.Huang, Kuo-Chen Chou, "iEnhancer-EL: Identifying enhancers and their strength with ensemble learning approach," Bioinformatics,34(22): 3835–3842, 2018.
  7. Wenzheng Bao, Chuan-An Yuan, Younhua Zhang, Kyungsook Han, Asoke K Nandi, Barry Honig, D.S.Huang,“Mutli-features prediction of protein translational modification sites,” IEEE/ACM Transactions on Computational Biology & Bioinformatics, 15(5): 1453-1460, 2018, DOI:10.1109/TCBB.2017.2752703.
  8. Bin Liu, Fan Weng, D.S.Huang, Kuo-Chen Chou, “iRO-3wPseKNC: Identifying DNA replication origins by three-window-based PseKNC,” Bioinformatics, 34(18): 3086-3093, 2018.
  9. Hai-Cheng Yi, Zhu-Hong You, D.S.Huang, Xiao Li, Tong-Hai Jiang, and Li-Ping Li, "A deep learning framework for robust and accurate prediction of ncRNA-protein interactions using evolutionary information," Molecular Therapy-Nucleic Acids, 11: 337-344, 2018.
  10. Lin Zhu, H.-B. Zhang, and D.S.Huang, "LMMO: A large margin approach for optimizing regulatory motifs," IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 15(3), 913-925, 2018.
  11. Yan-Bin Wang, Zhu-Hong You, Li-Ping Li, D.S.Huang, Feng-Feng Zhou, and Shan Yang. "Improving prediction of self-interacting proteins using stacked sparse auto-encoder with PSSM profiles," International Journal of Biological Sciences, 14(8): 983-991, 2018.
  12. Liangxin Gao, Wenzhen Bao, Hongbo Zhang, Chang-An Yuan and D.S.Huang, “Fast sequence analysis based on diamond sampling,” PloS One, 13(6), 2018, e0198922.
  13. Xianpeng Liang, Lin Zhu, and D.S.Huang,"Image segmentation fusion using weakly supervised trace-norm multi-task learning method," IET Image Processing, 2018, 12.7: 1079-1085.
  14. Guohui Chuai, Hanhui Ma, Jifang Yan, Ming Chen, Nanfang Hong, Dongyu Xue, Chi Zhou, Chenyu Zhu, Ke Chen, Bin Duan, Feng Gu, Sheng Qu, D.S.Huang, Jia Wei, Qi Liu, “DeepCRISPR: optimized CRISPR guide RNA design by deep learning,” Genome Biology, vol. 19, no. 1, pp. 80, June 26, 2018, DOI: 10.1186/s13059-018-1459-4.
  15. Xianpeng Liang, Lin Zhu, and D.S.Huang, "Optimization of gene set annotations using robust trace-norm multitask learning," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.15, no.3, pp.1016-1021.
  16. Saud Alguwaizani, Byungkyu Park, Xiang Zhou, D.S.Huangand Kyungsook Han, "Predicting interactions between virus and host proteins using repeat patterns and composition of amino acids," Journal of Healthcare Engineering, Vol.2018, Article ID 1391265, 9 pages.
  17. Bin Liu, Fan Yang, D.S.Huang, Kuo-Chen Chou, “iPromoter-2L: A two-layer predictor for identifying promoters and their types by multi-window-based PseKNC,” Bioinformatics, 34(1): 33-40, 2018, DOI:10.1093/bioinformatics/btx579.

 

2017

  1. Wenzheng Bao, Zhichao Jiang, D.S.Huang*, "Novel human microbe-disease association prediction using network consistency projection," BMC Bioinformatics, 18(S16), DOI: 10.1186/s12859-017-1968-2, 2017.
  2. Wen-Zheng Bao, Zhuhong You, D.S.Huang*, "CIPPEI: Computational identification of protein pupylation sites based on protein physicochemical properties and evolutionary information," Oncotarget, https://doi.org/10.18632/oncotarget.22335.
  3. Wei-Li Guo, D.S.Huang, “An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency”, Molecular BioSystems, DOI: 10.1039/C7MB00155J, 13(9): 1827-1837, 2017.
  4. Zhen Shen, You-Hua Zhang, Kyungsook Han, Asoke K. Nandi, Barry Honig, and D.S.Huang, “miRNA-disease association prediction with collaborative matrix factorization,” Complexity, vol. 2017, no. 2017: 1-9, 2017.
  5. Lin Yuan, Chang-An Yuan, and D.S.Huang, “FAACOSE: A fast adaptive ant colony optimization algorithm for detecting SNP epistasis,” Complexity, vol. 2017, no. 2017:1-10, 2017.
  6. Lin Yuan, Lin Zhu, Wei-Li Guo,Xiaobo Zhou, Youhua Zhang, Zhenhua Huang, and D.S.Huang, “Nonconvex penalty based low-rank representation and sparse regression for eQTL mapping,” IEEE/ACM Transactions on Computational Biology & Bioinformatics, vol. 14, no. 5, pp. 1154-1164. 2017.
  7. Su-Ping Deng, Shaolong Cao, D.S.Huang, and Yu-Ping Wang, “Identifying stages of kidney renal cell carcinoma by combining gene expression and DNA methylation data,”IEEE/ACM Transactions on Computational Biology & Bioinformatics, vol. 14, no. 5, pp. 1147-1153. 2017.
  8. Wenzheng Bao, Zhenhua Huang, Chang-An Yuan, D.S.Huang, "Pupylation sites prediction with ensemble classification model," International Journal of Data Mining and Bioinformatics (IJDMB), vol. 18, no. 2, pp. 91-104, 2017. 
  9. Lin Zhu, Hong-Bo Zhang, De-Shuang Huang, “Direct AUC optimization of regulatory motifs,” Bioinformatics, 33 (14): i243-i251, 2017.
  10. Paul Fergus, Abir Hussian, Dhiya Al-Jumeily, D.S.Huangand Nizar Bouguila, "Classification of caesarean section  and normal vaginal deliveries using foetal heart rate signals and advanced machine learning algorithms." BioMedical Engineering OnLine, 16: 89, 2017.
  11. Hongbo Zhang, Lin Zhu, D.S.Huang, "WSMD: weakly-supervised motif discovery in transcription factor ChIP-seq data," Scientific Reports, 7, 2017.
  12. Feng He, Guanghui Zhu, Yin-Ying Wang, Xing-Ming Zhao, D.S.Huang, “PCID: A novel approach for predicting disease comorbidity by integrating multi-scale data,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(3), pp.678-686, 2017.
  13. Lin Zhu, Su-Ping Deng, D.S.Huang, “Identifying spurious interactions in the protein-protein interaction networks using local similarity preserving embedding,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(2), pp.345-352, 2017.
  14. Fei Han, Chun Yang, Ya-Qi Wu, Jian-Sheng Zhu, Qing-Hua Ling, Yu-Qing Song, D.S.Huang, “A gene selection method for microarray data based on binary PSO encoding gene-to-class sensitivity information,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(1), pp.85-96, 2017. 
  15. Xianpeng Liang, Lin Zhu, and D.S.Huang, "Multi-task ranking SVM for image cosegmentaiton," Neurocomputing, 247, pp. 126-136, 2017.
  16. Xing Chen, Zhichao Jiang, Di Xie, D.S.Huang, Qi Zhao,Guiying Yan, Zhuhong You, "A novel computational model based on super-disease and miRNA for potential miRNA-disease association prediction,"  Molecular BioSystems, vol.13, pp.1202-1212, 2017.
  17. Zheng-Wei Li, Zhuhong You, Xing Chen, Li-Ping Li, D.S.Huang, Gui-Ying Yan, Ru Nie, Yu-An Huang. "Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier". Oncotarget, Vol.8, no.14, pp.23638-23649, 2017.
  18. Byungmin Kim, Saud Alguwaizani, Xiang Zhou, D.S.Huang, Byunkyu Park, and Kyungsook Han, "An improved method for predicting interactions between virus and human proteins,” Journal of Bioinformatics and Computational Biology, vol.15, no.1, 1650024 (17 pages), 2017.

 

2016

  1. Qing-Hua Ling, Yu-Qing Song, Fei Han, Dan Yang, D.S.Huang, “An improved ensemble of random vector functional link networks based on particle swarm optimization with double optimization strategy,” PloS One, 11(11), 2016, e0165803.
  2. -L. Guo, L. Zhu, S.-P. Deng, X.-M. Zhao, and D.S.Huang, “Understanding tissue-specificity with human tissue-specific regulatory networks,” Science China Information Sciences, vol. 59, no. 7, pp. 070105, 2016.
  3. Bing Wang, Hao Shen, Aiqin Fang, D.S.Huang, Changjun Jiang, Jun Zhang, Peng Chen, “A regression model for calculating the second dimension retention index in comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry,” Journal of Chromatography A, vol.1451, pp.127-134, 2016.
  4. Ji-Yong An, Zhu-Hong You, Xing Chen, D.S.Huang*, Zheng-Wei Li, Gang Liu, Yin Wang. "Identification of self-interacting proteins by exploring evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix," Oncotarget, vol. 7, no. 50, pp. 82440-82449. 2016.
  5. Yu-An Huang, Xing Chen, Zhuhong You, D.S.Huang, and Keith C. C.Chan, “ILNCSIM: improved lncRNA functional similarity calculation model,” Oncotarget, vol.7, no.8, pp.25902-25914, 2016.
  6. Wen Jiang, D.S.Huang, Shenghong Li, “Random-walk based solution to triple level stochastic point location problem,” IEEE Trans. on Cybernetics, vol.46, no.6, pp.1438-1451, 2016.
  7. Su-Ping Deng, Lin Zhu, and D.S.Huang, “Predicting hub genes associated with cervical cancer through gene co-expression networks,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 13, no.1, pp. 27-35, 2016.
  8. Lin Zhu, Weili Guo, Su-Ping Deng, and D.S.Huang, "ChIP-PIT: Enhancing the analysis of ChIP-Seq data using convex-relaxed pair-wise interaction tensor decomposition," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 13, no.1, pp. 55-63, 2016.

 

2015

  1. Su-Ping Deng, D.S.Huang, "An integrated strategy for functional analysis of microbial communities based on gene ontology and 16S rRNA gene," International Journal of Data Mining and Bioinformatics (IJDMB),vol.13, no.1: 63-74, 2015. 
  2. Lin Zhu, S.P.Deng, D.S.Huang,“A two-stage geometric method for pruning unreliable links in protein-protein networks,” IEEE Transactions on NanoBioscience, vol. 14, no.5, pp. 528-534, 2015.
  3. Zhiwei Ji, Guanmin Meng, D.S.Huang, Xiaoqiang Yue, and Bing Wang, "NMFBFS: A NMF-based feature selection method in identifying pivotal clinical symptoms of hepatocellular carcinoma," Computational and Mathematical Methods in Medicine Volume, Article ID 846942, 12 pages, 2015.
  4. Zhiwei Ji, Dan Wu, Weiling Zhao, Huiming Peng, Shengjie Zhao, D.S.Huang, and Xiaobo Zhou, “Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach,” Scientific Reports, 5:13291.
  5. Hai Min, Xiao-Feng Wang, D.S.Huang, Jing Jin, Hong-Zhi Wang and Hai Li,“Level set method for image segmentation based on moment competition,” Journal of Electronic Imaging, vol. 24, no.3, 2015.
  6. Lin Yuan, Chun-Hou Zheng, Jun-Feng Xia, D.S.Huang,"Module based differential coexpression analysis method for type 2 diabetes," BioMed Research International, Volume 2015, Article ID 836929, 8 pages.
  7. Jinyong Im, Narankhuu Tuvshinjargal, Byungkyu Park, Wook Lee, D.S.Huang, Kyungsook Han, “PNImodeler: web server for inferring proteinbinding nucleotides from sequence data,” BMC Genomics, 2015, 16 (Suppl 3):S6.
  8. Su-Ping Deng, Lin Zhu, D.S.Huang, “Mining the bladder cancer-associated genes by an integrated strategy for the construction and analysis of differential co-expression networks,” BMC Genomics, 2015, 16 (Suppl 3):S4.

 

2014

  1. Xing-Ming Zhao,Ke-Qin Liu, Guanghui Zhu,, Feng He,, Béatrice Duval,, Jean-Michel Richer, D.S.Huang, Chang-Jun Jiang,Jin-Kao Hao and Luonan Chen, “Identifying cancer-related microRNAs based on gene expression data,” Bioinformatics, oi:10.1093/bioinformatics/btu811, 31 (8): 1226-1234, 20
  2. Su-Ping Deng, D.S.Huang, “SFAPS: an R package for structure/function analysis of protein sequences based on informational spectrum method,” Methods,vol. 69, no. 3: 207-212, 2014. 
  3. D.S.Huang, Lei Zhang,Kyungsook Han, Suping Deng, Kai Yang, Hongbo Zhang, " Prediction of protein-protein interactions based on protein-protein correlation using least squares regression," Current Protein & Peptide Science, vol. 15, no. 6: 553-560, 2014.
  4. Zhiwei Ji, Jing Su, Chenglin Liu, Hongyan Wang, D.S.Huang, Xiaobo Zhou, “Integratinggenomics and proteomics data to predict drug effects using binary linear programming,” PLOS ONE, 9(7): e102798.
  5. Bing Wang and D.S.Huang, Changjun Jiang, "A new strategy for protein interface identification using manifold learning method," IEEE Transactions on NanoBioscience, vol.13, no.2: 118-123, 2014.
  6. Lin Zhu, D.S.Huang,“A Rayleigh–Ritz style method for large-scale discriminant analysis,” Pattern Recognition, vol.47: 1698-1708, 2014.

 

2013

  1. Byungkyu Park, Guangyu Cui, Hyunjin Lee, D.S.Huangand Kyungsook Han, “PPISearchEngine: Gene ontology-based search for protein-protein interactions,” Computer Methods in Biomechanics and Biomedical Engineering, vol. 16, no, 7, 691-698, 2013.
  2. Lin Zhu, Zhu-Hong You, D.S.Huang,“Increasing the reliability of protein-protein interaction networks via non-convex semantic embedding,”Neurocomputing, vol.121: 99-107, 2013.
  3. Hong-Jie Yu, D.S.Huang, “Descriptors for DNA sequences based on joint diagonalization of their feature matrices from dinucleotide physicochemical properties,” Tsinghua Science and Technology, vol.18, no.5, ISSNll1007-0214ll03/11,llpp. 446-453, October 2013.
  4. D.S.Huang, Hong-Jie Yu, “Normalized feature vectors: A novel alignment-free sequence comparison method based on the numbers of adjacent amino acids,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.10, no.2, pp.457-467, 2013.
  5. Lin Zhu, D.S.Huang, “Efficient optimally regularized discriminant analysis,” Neurocomputing, vol.117, pp.12-21, 2013.
  6. Hong-Jie Yu, D.S.Huang, “Graphical representation for DNA sequences via joint diagonalization of matrix pencil,” IEEE Journal of Biomedical and Health Informatics, vol.17, no.3, pp.503-511, 2013.
  7. Jian-Xun Mi, D.S.Huang, Bing Wang, Xingjie Zhu, “The nearest-farthest subspace classification for face recognition,” Neurocomputing, vol.113, pp.241-250, 2013.
  8. Can-Yi Lu, and D.S.Huang, “Optimized projections for sparse representation based classification,” Neurocomputing, vol.113, pp.213-219, 2013.
  9. Lin Zhu, Zhu-Hong You, D.S.Huangand Bing Wang, “t-LSE:A Novel Robust Geometric Approach for Modeling Protein-Protein Interaction Networks,”PLOS ONE, 8(4): e58368, 2013.

 

2012

  1. Hong-Jie Yu, D.S.Huang, “Novel graphical representation of genome sequence and its applications in similarity analysis,” Physica A-Statistical Mechanics and Its Applications, vol.391, no.23, pp.6128-6136, 2012.
  2. Rong-Xiang Hu, Wei Jia,Haibin Ling, D.S.Huang, “Multiscale distance matrix for fast plant leaf recognition, ” IEEE Trans. on Image Processing, vol.21, no.11, pp. 4667 - 4672, 2012.
  3. Yang Zhao, and D.S.Huang, “Completed local binary count for rotation invariant texture classification,” IEEE Trans. on Image Processing, vol.21, no.10, pp. 4492 - 4497, 2012.
  4. D.S.Huang, and Wen Jiang, “A general CPL-AdS methodology for fixing dynamic parameters in dual environments,” IEEE Trans. on Systems, Man and Cybernetics - Part B, vol.42, no.5, pp.1489-1500, 2012.
  5. Ying-Ke Lei, Zhu-Hong You, Zhen Ji, Lin Zhu, and D.S.Huang, "Assessing and predicting protein interactions by combining manifold embedding with multiple information integration, "BMC Bioinformatics, vol.13, S7, 2012.
  6. Hong-Jie Yu, D.S.Huang, “Novel 20-D descriptors of protein sequences and it's applications in similarity analysis,” Chemical Physics Letters, vol.531, pp.261-266, 2012.
  7. Lei Tang, Jing Su, D.S.Huang, Daniel Y. Lee, King C. P. Li and Xiaobo Zhou, "An integrated multi-scale mechanistic model for cancer drug therapy," International Scholarly Research Network ISRN Biomathematics,Vol. 2012, Article ID: 818492, 12 pages, 2012.
  8. Shu-Lin Wang, Yihai Zhu, Wei Jia, and D.S.Huang," Robust classification method of tumor subtype by using correlation filters," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.9, no.2, pp.580-591, 2012.

 

2011

  1. Chun-Hou Zheng, Lei Zhang, Vincent To-Yee Ng, Simon Chi-Keung Shiu, and D.S.Huang, “Molecular pattern discovery based on penalized matrix decomposition,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.8, no.6, pp.1592-1603, 2011.
  2. Chun-Hou Zheng, Lei Zhang, Vincent To-Yee Ng, Simon Chi-Keung Shiu, and D.S.Huang, “Metasample-based sparse representation for tumor classification,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.8, no.5, pp.1273-1282, 2011.
  3. Marcos G. Quiles, DeLiang Wang, Liang Zhao, Roseli A. F. Romero, and D.S.Huang, ”Selecting salient objects in real scenes: An oscillatory correlation model,” Neural Networks, vol. 24, no.1, pp. 54-64, 2011.

 

2010

  1. Bo Li, Chun-Hou Zheng, D.S.Huang, Lei Zhang, and Kyungsook Han, “Gene expression data classification using locally linear discriminant embedding,” Computers in Biology and Medicine,vol. 40, no.10, pp. 802-810, 2010.
  2. Zhu-Hong You, Ying-Ke Lei, D.S.Huang, and Xiaobo Zhou, “Using manifold embedding for assessing and predicting protein interactionsfrom high-throughput experimental data,” Bioinformatics, 26(21):2744-2751, 2010.
  3. Jie Gui, Wei Jia, Ling Zhu, Shu-Ling Wang, and D.S.Huang, “Locality preserving discriminant projections for face and palmprint recognition,” Neurocomputing, vol.73, nos.13-15, pp.2696-2707, 2010.
  4. Zhu-Hong You, Zheng Yin, Kyungsook Han, D.S.Huang,and Xiaobo Zhou, "A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network", BMC Bioinformatics, vol.11, 343, 2010.
  5. Jun-Feng Xia, Xing-Ming Zhao, Jiangning Song and D.S.Huang, “APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility,” BMC Bioinformatics, vol.11, 174, 2010.
  6. Jun-Feng Xia, Xing-Ming Zhao, and De-Shuang Huang, “Predicting protein-protein interactions from protein sequences using meta predictor,” Amino Acids, vol. 39, no.5, pp.1595–1599, 2010.
  7. Rong-Xiang Hu, Wei Jia,De-Shuang Huang, Ying-Ke Lei, “Maximum margin criterion with tensor representation, ” Neurocomputing, vol.73, nos.10-12, pp.1541-1549, 2010.
  8. Xing-Ming Zhao, Yiu-Ming Cheung, and D.S.Huang,“Analysis of gene expression data using RPEM algorithm in normal mixture model with dynamic adjustment of learning rate,”International Journal of Pattern Recognition and Artificial Intelligence, vol.24, no.4, pp.651-666, 2010.
  9. Fei Han, Qing-Hua Ling, and D.S.Huang, “An improved approximation approach incorporating particle swarm optimization and a priori information into neural networks,” Neural Computing & Applications, vol. 19, no.2, pp. 255-261, 2010.
  10. Shan-Wen Zhang, D.S.Huang, and Shu-Lin Wang, “A method of tumor classification based on wavelet packet transformsand neighborhood roughset,” Computers in Biology and Medicine,vol. 40, no.4, pp. 430-437, 2010.
  11. Shu-Lin Wang, Xueling Li, Shanwen Zhang, Jie Gui, and D.S.Huang, “Tumor classification by combining PNN classifier ensemble with neighborhood rough set based gene reduction,” Computers in Biology and Medicine,vol. 40, no.2, pp. 179-189, 2010.
  12. Xiao-Feng Wang, D.S.Huangand Huan Xu, "An efficient local Chan-Vese model for image segmentation," Pattern Recognition, vol. 43, no.3, pp. 603-618, 2010.
  13. Jun-Feng Xia, Kyungsook Han, and D.S.Huang, “Sequence-based prediction of protein-protein interactions by means of rotation forest and autocorrelation descriptor,” Protein and Peptide Letters, vol.17, no.1, pp. 137-145,2010.
  14. Ming-Guang Shi, Jun-Feng Xia, Xue-Ling Li and D.S.Huang, ”Predicting protein-protein interactions from sequence using correlation coefficient and high-quality interaction dataset,” Amino Acids, vol. 38, no.3, pp.891-899, 2010.

 

2009

  1. Bo Li, Chao Wang and D.S.Huang,“Supervised feature extraction based on orthogonal discriminant projection,” Neurocomputing, vol. 73, nos.1-3, pp 191-196, 2009.
  2. Xiao-Feng Wang, D.S.Huang, "A novel density-based clustering framework by using level set method," IEEE Transactions on Knowledge and Data Engineering, vol. 21, no.11, pp 1515-1531, 2009.
  3. Chun-Hou Zheng, D.S.Huang, Lei Zhang, and Xiang-Zhen Kong, “Tumor clustering using non-negative matrix factorization with gene selection,” IEEE Transactions on Information Technology in Biomedicine,vol. 13, no.4, pp 599-607, 2009.
  4. Jisu Kim, D.S.Huangand Kyungsook Han, “Finding motif pairs in the interactions between heterogeneous proteins via bootstrapping and boosting,” BMC Bioinformatics, 10:S57, 2009.

 

2008

  1. D.S.Huang, Ji-Xiang Du, “A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks,” IEEE Transactions on Neural Networks,vol. 19, no.12, pp 2099-2115, 2008.
  2. Chao Wang, B. Li and D.S.Huang, “Non-small cell lung cancer prediction based on orthogonal discrimination projection,” Journal of Computational Information Systems, vol. 4, no.5, pp.1861-1867, 2008.
  3. Xiao-Feng Wang, D.S.Huang, Ji-Xiang Du, Huan Xu, Laurent Heutte, “Classification of plant leaf images with complicated background,” Applied Mathematics and Computation, vol. 205, no.2, pp 916-926, 2008.
  4. Xiao-Feng Wang, D.S.Huang,“A novel multi-layer level set method for image segmentation,” Journal of Universal Computer Science, vol.14, no.14, pp.2428-2452, 2008.
  5. Bo Li, Chun-Hou Zheng, and D.S.Huang,“Locally linear discriminant embedding: An efficient method for face recognition,” Pattern Recognition, vol.41, no.12, pp. 3813-3821, 2008.
  6. Bo Li, D.S.Huang, Chao Wangand Kun-Hong Liu, “Feature extraction using constrained maximum variance mapping,” Pattern Recognition, vol.41, no.11, pp. 3287-3294, 2008.
  7. Chun-Hou Zheng, D.S.Huang, Xiang-Zhen Kong, Xing-Ming Zhao, “Gene expression data classification using consensus independent component analysis,” Genomics Proteomics & Bioinformatics, vol.6, no.2, pp. 74-82, 2008.
  8. Ming-Guang Shi, D.S.Huangand Xue-Ling Li, “A protein interaction network analysis for yeast integral membrane protein,” Protein and Peptide Letters, vol. 15, no. 7, pp. 692-699, 2008.
  9. Guangyu Cui, Yu Chen, D.S.Huang, and Kyungsook Han, "An algorithm for finding functional modules and protein complexes in protein-protein interaction networks," Journal of Biomedicine and Biotechnology, vol.2008, article ID 860270, 10 pages, 2008.
  10. Peng Chen, Kyungsook Han, Xueling Li, and D.S.Huang, ”Predicting key long-range interaction sites by B-factors,” Protein and Peptide Letters, vol. 15, no. 5, pp.478-483, 2008.
  11. Kun-Hong Liu, and D.S.Huang+,“Cancer classification using rotation forest,” Computers in Biology and Medicine, vol. 38, no. 5, pp.601-610, 2008.
  12. Peng Chen, D.S.Huang, Xing-Ming Zhao, and Xueling Li, ”Predicting contact map using radial basis function neural network with conformational energy function,” International Journal of Bioinformatics Research and Applications, vol. 4, no. 2,pp.123-136, 2008.
  13. Kun-Hong Liu, Yong Xu, D.S.Huang,and Min Cheng, “Grooming of dynamic traffic in WDM star and tree networks using a genetic algorithm,” Photonic Network Communications, vol.15, no. 2, April, pp.111-121, 2008.
  14. Fei Han, D.S.Huang, “A new constrained learning algorithm for function approximation by encoding a priori information into feedforward neural networks,” Neural Computing and Applications, vol.17, nos.5-6, pp.433-439, 2008.
  15. Wei Jia, D.S.Huang,and David Zhang, “Palmprint verification based on robust line orientation code,” Pattern Recognition, vol.41, no.5, pp. 1521-1530, 2008.
  16. D.S.Huang, Wei Jia, and David Zhang,“Palmprint verification based on principal lines,” Pattern Recognition, vol.41, no.4, pp. 1316-1328, 2008.
  17. Fei Han, Qing-Hua Ling, and D.S.Huang, “Modified constrained learning algorithms incorporating additional functional constraints into neural networks,” Information Sciences, vol.178, no.3, pp.907-919, 2008.
  18. Zhigang Zeng; D.S.Huang, Zengfu Wang,“Pattern memory analysis based on stability theory of cellular neural networks,” Applied Mathematical Modelling,vol.32, no.1, pp. 112-121, 2008.

 

2007

  1. Zhong-Qiu Zhao, D.S.Huang, “Palmprint recognition with 2DPCA+PCA based on modular neural networks,” Neurocomputing, vol.71, nos.1-3,pp. 448-454, 2007.
  2. D.S.Huang, Jian-Xun Mi, “A new constrained independent component analysis method,” IEEE Trans. On Neural Networks,vol.18, no.5, pp.1532-1535, 2007.
  3. Hong-Qiang Wang, Hau-San Wong, D.S.Huangand Jun Shu, “Extracting gene regulation information for cancer classification,” Pattern Recognition, vol.40, no.12, pp. 3379-3392, 2007.
  4. Chun-Hou Zheng, D.S.Huang, Kang Li, George W Irwin and Zhan-Li Sun, "MISEP method for Post-Nonlinear Blind Source Separation,” Neural Computation, vol.19, no.9, pp.2557-2578, 2007.
  5. Cătălin Căleanu, D.S.Huang, Vasile Gui, Virgil Tiponuţ and Valentin Maranescu, “Interest operator vs. Gabor filtering for facial imagery classification,” Pattern Recognition Letters, vol.28, no.8, pp.950-956, 2007.
  6. Peng Chen, Bing Wang, Hau San Wong, and D.S.Huang, “Prediction of protein B-factors using multi-class bounded SVM,” Protein and Peptide Letters, vol.14, no.2, pp.185-190, 2007.
  7. Zhong-Qiu Zhao, D.S.Huang, “A mended hybrid learning algorithm for radial basis function neural networks to improve generalization capability,” Applied Mathematical Modelling, vol.31, no.7,pp. pp.1271-1281, 2007.
  8. Ji-Xiang Du, D.S.Huang, Xiao-Feng Wang, Xiao Gu, “Shape recognition based on neural networks trained by differential evolution algorithm,” Neurocomputing,vol.70, nos.4-6, pp. 896-903, 2007.

 

2006

  1. Ji-Xiang Du, D.S.Huang,Guo-Jun Zhang and Zeng-Fu Wang, “A novel full structure optimization algorithm for radial basis probabilistic neural networks,” Neurocomputing, vol.70, nos.1-3, pp. 592-596, 2006.
  2. Pei Shun, and D.S.Huang, "Cooperative competition clustering for gene selection", Journal of Cluster Science, vol. 17, no. 4, pp.637-651, December 2006.
  3. Jian-Xun Peng, Kang Li and D.S.Huang, “A hybrid forward algorithm for RBF neural network construction,”IEEE Trans. On Neural Networks,vol.17, no.6, pp. 1439-1451, 2006.
  4. Bing Wang, Hau San Wong, and D.S.Huang, “Inferring protein-protein interacting sites using residue conservation and evolutionary information,” Protein and Peptide Letters, vol.13, no.10, pp. 999-1005, 2006.
  5. D.S.Huang, Xin Huang, “Improved performance in protein secondary structure prediction by combining multiple predictions,” Protein and Peptide Letters, vol.13, no.10, pp. 985-991, 2006.
  6. D.S.Huang, Xing-Ming Zhao, Guang-Bin Huang, and Yiu-Ming Cheung, “Classifying protein sequences using hydropathy blocks,” Pattern Recognition, vol.39, no.12, pp.2293–2300,2006.
  7. Chun-Hou Zheng, D.S.Huang, and Li Shang, “Feature selection in independent component subspace for microarray data classification,” Neurocomputing,vol.69, nos.16-18, pp.2407-2410, 2006.
  8. Jun Zhang, D.S.Huang,Tat-Ming Lok, and Michael R. Lyu, “A novel adaptive sequential niche technique for multimodal function optimization,” Neurocomputing, vol.69, nos.16-18, pp.2396-2401, 2006.
  9. Fei Han, D.S.Huang, "Improved extreme learning machine for function approximation by encoding a priori information," Neurocomputing,vol.69, nos.16-18, pp.2369-2373, 2006.
  10. D.S.Huang, Chun-Hou Zheng, “Independent component analysis based penalized discriminant method for tumor classification using gene expression data,” Bioinformatics, vol.22, no.15, pp.1855-1862, 2006.
  11. Ji-Xiang Du, D.S.Huang,Xiao-Feng Wang, and Xiao Gu, “Computer-aided plant species identification (CAPSI) based on leaf shape matching technique,” Transactions of the Institute of Measurement and Control, vol. 28, no. 3, pp. 275-284, 2006.
  12. Li Shang, D.S.Huang,Ji-Xiang Du, and Chun-Hou Zheng, " Palmprint recognition using FastICA algorithm and radial basis probabilistic neural network," Neurocomputing, vol.69, nos.13-15, pp. 1782-1786, 2006.
  13. Jing-Jing Li, D.S.Huang, Bing Wang, Peng Chen, “Identifying Protein-Protein Interfacial Residues in Heterocomplexes Using Residue Conservation Scores,” International Journal of Biological Macromolecules, vol.38, nos.3-5, pp.241-247, 2006.
  14. Jing-Jing Li, D.S.Huang, Tat-Ming Lok, Michael R. Lyu, Yi-Xue Li and Yun-Ping Zhu, “Network analysis of the protein chain tertiary structures of heterocomplexes,” Protein and Peptide Letters, vol.13, no.4, pp. 391-396, 2006.
  15. Fei Han, D.S.Huang, “Improved constrained learning algorithms by incorporating additional functional constraints into neural networks,” Applied Mathematics and Computation, vol. 174, no.1, pp 34-50, 2006.
  16. Fei Han, D.S.Huang, Zhi-Hua Zhu, and Tie-Hua Rong, "The forecast of the postoperative survival time of patients suffered from non-small cell lung cancer based on PCA and extreme learning algorithm," International Journal of Neural Systems, vol. 16, no. 1, pp.39-46, 2006.
  17. Zhan-Li Sun, D.S.Huang, and Chun-Hou Zheng, Li Shang, “Optimal selection of time lags for temporal blind source separation based on genetic algorithm,” Neurocomputing, vol.69, nos.7-9, pp.884–887, 2006.
  18. Chun-Hou Zheng, D.S.Huang,Zhan-Li Sun, Michael R. Lyu, and Tat-Ming Lok, "Nonnegative independent component analysis based on minimizing mutual information technique," Neurocomputing, vol.69, nos.7-9, pp.878–883, 2006.
  19. Li Shang, D.S.Huang,Chun-Hou Zheng, and Zhan-Li Sun, "Noise removal using a novel non-negative sparse coding shrinkage technique," Neurocomputing, vol.69, nos.7-9, pp.874–877, 2006.
  20. Bing Wang, Peng Chen, D.S.Huang, Jing-Jing Li, Tat-Ming Lok, Michael R. Lyu, “Predicting protein interaction sites from residue spatial sequence profile and evolution rate," FEBS Letters, vol.580, no.2,pp. 380-384, 2006.
  21. Hong-Qiang Wang,D.S.Huang, “Regulation probability method for gene selection,” Pattern Recognition Letters, vol.27, no.2, pp.116-122, 2006.

 

2005

  1. Hong-Qiang Wang, and D.S.Huang, “Non-linear cancer classification using a modified radial basis function classification algorithm,” Journal of Biomedical Science, vol.12, no.5, pp.819-826, 2005.
  2. Guang-Bin Huang, K. Z. Mao, Chee-Kheong Siew, and D.S.Huang, “Fast modular network implementation for support vector machines,” IEEE Transactions on Neural Networks,vol. 16, no. 6, pp.1651-1663, 2005.
  3. Zhan-Li Sun, D.S.Huang, Chun-Hou Zheng and Li Shang, “Using batch algorithm for kernel blind source separation,” Neurocomputing, vol.69, nos. 1-3,pp.273-278, 2005.
  4. Xing-Ming Zhao, Yiu-Ming Cheung, and D.S.Huang, “A novel approach to extracting features from motif content and protein composition for protein sequence classification,” Neural Networks, vol.18, no.8, pp.1019-1028, 2005.
  5. Guang-Zheng Zhang, D.S.Huang, Yunping Zhu and Yixue Li, "Improving protein secondary structure prediction by using residue conformational classes,” Pattern Recognition Letters, vol.26, no.15, pp.2346-2352, 2005.
  6. Huang, D.S.Huang, Gunang-Zheng Zhang, Yun-Ping Zhu and Yi-Xue Li, “Prediction of protein secondary structure using improved two-level neural network architecture,” Protein and Peptide Letters, vol.12, no.8, pp.805-811, 2005.
  7. Zhigang Zeng; D.S.Huang, Zengfu Wang,“Global stability of a general class of discrete-time recurrent neural networks," Neural Processing Letters, vol.22, no.1, pp.33-47, 2005.
  8. Xing-Ming Zhao, Yiu-Ming Cheung and D.S.Huang, “A novel markov pairwise protein sequence alignment method for sequence comparison,” Protein & Peptide Letters, vol.12, no.7, pp.665-669, 2005.
  9. Bing-Yu Sun, D.S.Huangand Hai-Tao Fang, “A novel robust regression approach of Lidar signal based on least squares support vector machine,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 19, no. 5, pp.715-729, 2005.
  10. Hong-Qiang Wang,D.S.Huang, “A gene selection algorithm based on the gene regulation probability using MLE,” Biotechnology Letters, vol.27, no.8, pp.597-603, 2005.
  11. Hong-Qiang Wang, D.S.Huang, Bin Wang, “Optimization of radial basis function classifiers using simulated annealing algorithm for cancer classification,” IEE Electronics Letters, vol.41, no.11, pp.630-632, 2005.
  12. Hai-Tao Fang and D.S.Huang, “Extracting mode components in laser intensity distribution by independent component analysis,” Applied Optics, vol.44, no.18, pp.3646-3653, June 2005.
  13. Zhigang Zeng; D.S.Huang, Zengfu Wang, “Memory pattern analysis of cellular neural networks,” Physics Letters A, vol.342, nos.1-2, pp.114–128, 2005.
  14. Zhan-Li Sun, D.S.Huang,and Yiu-Ming Cheung, “Extracting nonlinear features for multispectral images by FCMC and KPCA,” Digital Signal Processing, vol.15, no.4, 331-346, 2005. 
  15. Guang-Zheng Zhang, D.S.Huangand Z.H. Quan, "Combining a binary input encoding scheme with RBFNN for globulin protein inter-residue contact map prediction," Pattern Recognition Letters, vol.26, no.10, pp.1543-1553, July 2005.
  16. Xing-Ming Zhao, D.S.Huang, Yiu-Ming Cheung,“A novel hybrid GA/RBFNN technique for protein classification,” Protein & Peptide Letters, vol.12, no.4, pp.383-386, MAY 2005.
  17. D.S.Huang,Zheru Chi and Wan-Chi Siu, “A case study for constrained learning neural root finders,” Applied Mathematics and Computation, vol.165, no. 3, pp.699-718, 2005.
  18. Zhan-Li Sun, D.S.Huang, Yiu-Ming Cheung, Jiming Liu and Guang-Bin Huang, “Using FCMC, FVS and PCA techniques for feature extraction of multispectral images,” IEEE Geoscience and Remote Sensing Letters, vol.2, no.2, pp.108-112, 2005.
  19. D.S.Huang, Horace H.S.Ip, Law Ken C K and Zheru Chi, ”Zeroing polynomials using modified constrained neural network approach,” IEEE Trans. On Neural Networks,vol.16, no.3, pp.721-732, 2005.
  20. Hai-Tao Fang and D.S.Huang, Yong-Hua Wu, “Anti-noise approximation of Lidar signal with wavelet neural networks,” Applied Optics, vol.44, no.6,pp.1077-1083, 2005.
  21. Xia Huang, Jinde Cao and D.S.Huang,“LMI-based approach for delay-dependent exponential stability analysis of BAM neural networks,” Chaos, Solitons and Fractals, vol.24,no.3, pp.885–898, 2005.
  22. D.S.Huang, Horace H.S.Ip, Law Ken C K, Zheru Chiand H.S.Wong, ”A new partitioning neural network model for recursively finding arbitrary roots of higher order arbitrary polynomials,” Applied Mathematics and Computation, vol.162, no.3, pp.1183-1200, 2005.
  23. Bing-Yu Sun, D.S.Huangand Hai-Tao Fang, "Lidar signal de-noising using least squares support vector machine," IEEE Signal Processing Letters, vol.12, no.2, pp.101-104, 2005.
  24. Jinde Cao, D.S.Huang, and Yuzhong Qu, "Global robust stability of delayed recurrent neural networks," Chaos, Solitons and Fractals, vol.23, no.1, pp.221–229, 2005.
  25. D.S.Huang,Wen-Bo Zhao, "Determining the centers of radial basis probabilistic neural networks by recursive orthogonal least square algorithms," Applied Mathematics and Computation, vol.162, no.1, pp.461-473, 2005.

 

2004

  1. Guang-Zheng Zhang, D.S.Huang, “Prediction of inter-residue contacts map based on genetic algorithm optimized radial basis function neural network and binary input encoding scheme,” Journal of Computer Aided Molecular Design, vol.18, no.12, pp.797-810, Dec 2004.
  2. B.Zhao, D.S.Huang, Ji-Yan Du and Li-Ming Wang, “Genetic optimization of radial basis probabilistic neural networks,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 18, no. 8, pp. 1473-1500, 2004.
  3. Guang-Zheng Zhang and D.S.Huang,“Inter-residue spatial distance prediction by using intergrating GA with RBFNN,” Protein and Peptide Letters, vol.11, no.6, pp.571-576, 2004.
  4. Zhong-Qiu Zhao, D.S.Huangand Bing-Yu Sun, "Human face recognition based on multi-features using neural networks committee," Pattern Recognition Letters, vol.25, no.12, pp.1351-1358, 2004.
  5. Zhigang Zeng; D.S.Huang, Zengfu Wang,“Attractability and location of equilibrium point of cellular neural networks with time-varying delays,” International Journal of Neural Systems, Vol. 14, No. 5, pp.337-345, 2004.
  6. D.S.Huang, Horace H.S.Ip and Zheru Chi, ”A neural root finder of polynomials based on root moments,” Neural Computation, vol.16, no.8, pp.1721-1762, 2004. 
  7. D.S.Huang, “A constructive approach for finding arbitrary roots of polynomials by neural networks,” IEEE Transactions on Neural Networks, vol.15, no.2, pp.477-491, 2004.
  8. Hai-Tao Fang and D.S.Huang, “Noise reduction in Lidar signal based on discrete wavelet transform,” Optics Communications, vol. 233, no.1-3, pp 67-76, 2004.
  9. Hai-Tao Fang and D.S.Huang, “Lidar signal de-noising based on wavelet trimmed thresholding technique,” Chinese Optics Letters, vol.2, no.1, 1-3, 2004.

 

2003

  1. Lin Guo, D.S.Huang, Wenbo Zhao, “Combining genetic optimisation with hybrid learning algorithm for radial basis function neural networks,” IEE Electronics Letters, vol. 139, no.22, pp.1600- 1601, 2003.
  2. D.S.Huang, Horace H.S.Ip, Zheru Chiand H.S.Wong, “Dilation method for finding close roots of polynomials based on constrained learning neural networks,” Physics Letters A, vol.309, no.5-6, pp.443-451, 2003.

 

1999

  1. D.S.Huangand S.D.Ma,“Linear and nonlinear feedforward neural network classifiers: A comprehensive understanding,”Journal of Intelligent Systems, vol.9, no.1, pp.1-38,1999.
  2. D.S.Huang,“A novel forward-backward smoothing based learning subspace method for recognition of radar targets,”International Journal of Pattern Recognition and Artificial Intelligence, vol.13, no.1, pp.65-83, 1999.
  3. D.S.Huang,“Application of generalized radial basis function networks to recognition of radar targets,”International Journal of Pattern Recognition and Artificial Intelligence, vol.13, no.6, pp.945-962, 1999.
  4. D.S.Huang,“The‘bottleneck behaviour in linear feedforward neural network classifiers and their breakthrough,”Journal of Computer Science and Technology, vol.14, no.1, pp.34-43, 1999.
  5. D.S.Huang,“Radial basis probabilistic neural networks: Model and application,”International Journal of Pattern Recognition and Artificial Intelligence, 13(7), pp.1083-1101, 1999.

 

1998

  1. D.S.Huang,“The local minima free condition of feedforward neural networks for outer-supervised learning,”IEEE Trans on Systems, Man and Cybernetics, vol.28B, no.3, 1998, pp.477-480.
  2. D.S.Huangand Y.Q.Han,“A detection method of high resolution radar targets based on position correlation,”Journal of Electronics, 5(2), pp.107-115,1998.

 

1997

  1. D.S.Huang,“The united adaptive learning algorithm for the link weights and the shape parameters in RBFN for pattern recognition,”International Journal of Pattern Recognition and Artificial Intelligence, vol.11, no.6, pp.873-888, 1997.

 

1996

  1. D.S.Huang,“The statistical properties of the learning subspace methods for pattern recognition,”Transactions of Information Processing, vol.37, no.6, pp.1081-1087, 1996.
  2. D.S.Huang,“Generalization capabilities in feedforward neural networks for pattern recognition,”Journal of Beijing Institute of Technology, 5(2), pp.184-192,1996.

 

1995

  1. D.S.Huangand Z.Bao,“The study of recognition technique of radar targets one dimensional images based on radial basis function network,”Journal of Electronics, 12(3), pp.200-210,1995.

 

  • Chinese Journal Papers

    •  

    2006

     

    1. Li Shang, De-Shuang Huang, Chun-Hou Zheng, “Natural image denoising method based on nonnegative sparse coding shrinkage,” Journal of the University of Science and Technology of China, Vol.36,5,pp.497-501, 2006.
    2. Xiaofeng Wang, De-Shuang Huang, Ji-Xiang Du, and Guojun Zhang, “Feature extraction and recognition for leaf images,” Computer Engineering and Application, Vol.42,3,pp.190-193, 2006.
    3. Zhong-Hua Quan,De-Shuang Huang, and Guang-Zhen Zhang, “Approximate string match of special points in signatures and random forgery elimination,” Journal of Applied Sciences, Vol.24, No.2, 2006, pp.187-192.
    4. D.S.Huang, “The development and prospects of intelligent computing technology,” China Academic Journal, Vol.21, No.1, 2006, pp.46-52.

     

    2005

     

    1. Wen-Bo Zhao and D.S. Huang, “Structure optimization of radial basis probabilistic neural networks by the maximum absolute error combined with the micro-genetic algorithm,” Computer Research and Development, v.42, n.2, 2005, pp.179-187.

     

    2004

     

    1. Hai-Tao Fang and D.S. Huang, “3D visualization of the energy distribution of laser spot based on pseudo-color transform and the interpolation of grayscale,” Opto-Electronic Engineering, vol.31, no. 10, pp. 61-65, 2004.
    2. Wen-Bo Zhao and D.S. Huang, “The genetic optimization of the full structure of radial basis probabilistic neural networks,” Journal of Infrared and Millimeter Waves, Vol.23, No.2, pp.113-118, 2004.

     

    2003

     

    1. Wen-Bo Zhao, D.S.Huang, L.Guo, “The genetic optimization of radial basis probabilistic neural networks,”Journal of the University of Science and Technology of China, Vol.33, No.6, pp.733-744, 2003.
    2. Wen-Bo Zhao, D.S.Huang and Shukun Wang,“Training radial basis probabilistic neural networks based on unsupervised learning algorithm,”Pattern Recognition and Artificial Intelligence, Vol.16, No.4, pp.442-447, 2003.
    3. D.S.Huang, Zheru Chi, “A Partition-based Recursive Approach for finding Higher-Order Polynomial Roots using Constrained Learning Neural Networks,” Science in China (Series E), 33(12), pp.1115-1124, 2003.

     

    2002

     

    1. Z.Liang, X.G.He and D.S.Huang,“On the discussion of peceptron convergent theorem based single fuzzy neural networks,”Acta Electronica Sinica, 30(3), pp.407-409, 2002.

     

    2000

     

    1. Z.Liang, X.G.He and D.S.Huang, “A simple conjugate gradient learning algorithm for feedforward neural networks,”Journal of Beijing University of Aeronautics and Astronautics, 26(5), pp.596-599, 2000(EI, CSA).
    2. Z.Liang, X.G.He and D.S.Huang,“A superlinearly convergent BP algorithm for feedforward neural networks,”Journal of Software, 11(8), pp.1094-1096, 2000.

     

    1999

     

    1. D.S.Huang,“On the global optimal theory of the outer-supervised learning feedforward neural networks,”Acta Electronica Sinica, 27(4), pp.98-101,1999.

     

    1998

     

    1. D.S.Huang,“The study of classification mechanism of outer-supervised feedforward neural network classifiers,”Chinese Journal of Computers, 21(7), pp.650-655,1998.
    2. D.S.Huang,“A new model of radial basis probabilistic neural network: basic theory,”Computer Research and Development, Vol.35, No.2, pp.118-121,1998.
    3. D.S.Huang,“A new model of radial basis probabilistic neural network: case study,”Computer Research and Development, Vol.35, No.2, pp.122-127, 1998.
    4. D.S.Huang,“On the study of transformation properties of the hidden units of feedforward neural network classifiers,”Acta Electronica Sinica, 26(11), pp.99-103,1998.

     

    1997

     

    1. D.S.Huang,“The bottleneck and capability of linear supervised classifier,”Acta Electronica Sinica, vol.25, no.7, pp.63-67,1997.
    2. D.S.Huang and Y.Q.Han,“Position correlation based detection method of high resolution radar targets,”Journal of Electronics and Information, 19(5), pp.584-590,1997.

     

    1996

     

    1. D.S.Huang,“The pattern classification method for probabilistic neural network based on principal components analysis,”Journal of Beijing Institute of Technology, China, 16(1), pp.69-74,1996.

     

    1995

     

    1. D.S.Huang,“Radial basis function networks based recognition technique of range images of radar targets,”Journal of Electronics and Information, Vol.12, No.3, pp.200-210, 1995.
    2. D.S.Huang,“Application of wavelet transform to radar signal processing: potentialities and prospects,”Journal of Beijing Institute of Technology, China, Vol.15, No.2, pp.186-191, 1995.
    3. D.S.Huang,“The study of three kinds of new self-supervised learning subspace methods for pattern recognition,”Acta Electronica Sinica, China, Vol.23, No.7, pp.25-30,1995.
    4. D.S.Huang,“An analysis of the statistical properties on the self-supervised learning subspaces for pattern recognition,”Acta Electronica Sinica, China, Vol.23, No.9, pp.99-102,1995.

     

    1993

     

    1. D.S.Huang, B.T.Wei and X.H.Chen,“The study of the radiators identification technique for the anti-radiation missiles based on neural networks BSB models,”Journal of Systems Engineering and Electronics, China, Vol.15, No.5, pp.31-35, 1993.

     

    1992

     

    1. D.S.Huang and Z.Bao,“The study of spectral properties of millimeter wave metallic chaff echo signals,”Modern Radar, China, No.2, pp.98-105, 1992.
    2. D.S.Huang and Z.Bao,“The study of high resolution spatial spectral estimation based on forward and backward linear prediction total least squares,”Journal of Communications, China, Vol.13, No.4, pp.25-32, 1992.

     

    1991

     

    1. D.S.Huang,“Application of new technique of neural networks to electronics warfare,”Journal of Electronics Countermeasure, China, No.1, pp.1-7, 1991.
    2. D.S.Huang,“The computer simulation for the sequence with good performance-Good sequence,”Journal of Modern Communication Technology, China, No.1, pp.17-24,1991.
    3. D.S.Huang and K.Z.Chen, “A study of a fast frequency searching method,”Journal of Xidian University, China, Vol.18, No.4, pp.62-68, 1991.
    4. D.S.Huang,“Application of artificial neural networks to CCCI system,”Journal of Communication Technology and Development, China, No.1, pp.28-32,1991.
    5. D.S.Huang,“An analysis of single snapshot linear prediction spatial spectrum estimation based on total least square method,”Journal of Systems Engineering and Electronics, China, Vol.13, No.11, pp.35-40,1991.

     

    1990

     

    1. D.S.Huang, D.J.Zhu and B.T.Wei,“Application of fast adaptive algorithm combined with high speed processor to frequency estimate of frequency-hopping signals,”Journal of Electronics Countermeasure, China, No.1, pp.1-6, 1990.
    2. D.S.Huang and D.J.Zhu,“The study of error coded probability and effective jamming methods for countermeasuring 2FSK frequency-hopping station,”Journal of Electronics Countermeasure, China, No.3, pp.11-18, 1990.

     

  •  Chapters in Books

    •  

    2019

    1. Andong Li, Di Wu, D.S.Huang, Lijun Zhang, “Convolutional capsule-based network for person re-identification,” ICIC 2019, Lecture Notes in Computer Science (LNCS 11643), p 304-11, 2019.

     

    2018

    1. Si-Jia Zheng; Di Wu; Fei Cheng; Yang Zhao; Chang-An Yuan; Xiao Qin; D.S.Huang,“A simple and effective deep model for person re-identification,” ICIC 2018, Lecture Notes in Artificial Intelligence (LNAI 10956), 223-8, 2018.
    2. Di Wu, Si-Jia Zheng, Fei Cheng, Yang Zhao, Chang-An Yuan, Xiao Qin, Yong-Li Jiangand D.S.Huang, “A hybrid deep model for person re-identification,” ICIC2018, Part Ⅲ, LNAI 10956, pp.229-234, 2018.

     

    2014

    1. Lin Zhu, Zhu-Hong You, D.S.Huang, “Identifying spsurious interactions in the protein-protein interaction networks using local similarity preserving embedding,” The 10th International Symposium on Bioinformatics Research and Applications (ISBRA2014), June 28-30, Zhangjiajie, China, Lecture Notes in Bioinformatics (LNBI), 8492:138–148, 2014.

     

    1. Lin Zhu, D.S.Huang, “A new method for prediction of protein function by combining phylogenetic tree and mathematical inference,” The 10th International Symposium on Bioinformatics Research and Applications (ISBRA2014), June 28-30, Zhangjiajie, China, 2014.

     

    2013

     

    1. Kai Yang, D.S.Huang, “Mathematical inference and application of expectation-maximization algorithm in the construction of phylogenetic tree,” ICIC 2013, Lecture Notes in Artificial Intelligence, 7996: 260–266, 2013.

     

    2009

     

    1. Chao Wang, D.S.Huang, and Bo Li, “A novel local sensitive frontier analysis for feature extraction,” Lecture Notes in Artificial Intelligence. 5755: 556-565, 2009.

     

     

    2008

     

    1. Guo-Zhu Wen and D.S.Huang, “A novel spike sorting method based on semi-supervised learning,” Lecture Notes in Computer Science, Volume 5227, pp. 605-615, 2008.

     

    2007

     

    1. Sheng-Bo Guo, Ying Wang, Longnian Lin, Joe Tsien, D.S.Huang, ”Long-range temporal correlation in the spontaneous in vivo activity of interneuron in the mouse hippocampus,” Lecture Notes in Computer science ,Springer-Verlag, International Conference on Intelligent Computing 2007, Qingdao, Shandong, China, August 21-24, 2007, pp.1339-1344.

     

    2006

     

    1. Zhi-Kai Huang, D.S.Huang,Ji-Xiang Du, Zhong-Hua Quan, Shen-Bo Guo, “Bark classification based on Gabor filter features using RBPNN neural network,” Lecture Notes in Computer Science (Neural Information Processing - 13th International Conference, ICONIP 2006, Proceedings), Vol. 4233, 80-87, 2006.
    2. Guo-Jun Zhang, Ji-Xiang Du, D.S.Huang,Tat-Ming Lok, and Michael R. Lyu, “Adaptive nearest neighbor classifier based on supervised ellipsoid clustering,” Lecture Notes in Artificial Intelligence (LNAI), Springer-Verlag, Vol.4223, 582-585, 2006 (The 2nd International Conference on Natural Computation (ICNC'06) and the 3rd International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'06), Xi’an, September 24-28, 2006, China).
    3. Shun Pei, D.S.Huang, Kang Li, George W. Irwin, “Gene selection by cooperative competition clustering,” Lecture Notes in Bioinformatics, Springer-Verlag, Vol.4115, 464-474, 2006 (International Conference on Intelligent Computing, Kunming, August 16-19, China).
    4. Xing Yan, Lei Cao, D.S.Huang, Kang Li, George Irwin, “A novel feature fusion approach based on blocking and its application in image recognition,” Lecture Notes in Computer Science, Springer-Verlag, Vol.4113, 1085-1091, 2006 (International Conference on Intelligent Computing, Kunming, August 16-19, China).
    5. Xing-Ming Zhao, D.S.Huang, Shiwu Zhang, Yiu-ming Cheung, “Classifying G-protein coupled receptors with hydropathy blocks and support vector machines,” Lecture Notes in Bioinformatics, Springer-Verlag, Vol.4115, 593-602, 2006 (International Conference on Intelligent Computing, Kunming, August 16-19, China).
    6. Li Shang, D.S.Huang,Ji-Xiang Du, Zhi-Kai Huang, “Palmprint recognition using ICA based on winner-take-all network and radial basis probabilistic neural network,” Lecture Notes in Computer Science, Springer-Verlag, Vol.3972, 216 - 221, 2006(International Symposium on Neural Network, Chengdu, May 30-June 1, China).

     

    2005

     

    1. Li Shang, D.S.Huang, Chun-Hou Zheng, and Zhan-Li, Sun,“Image feature extraction based on an extended non-negative sparse coding neural network model,” Lecture Notes in Computer Science, Springer-Verlag, 3497:807-812, 2005(International Symposium on Neural Network, Chongqing, May 30-June 1, China).
    2. Chun-Hou Zheng, D.S.Huang,Zhan-Li Sun and Li Shang, “Post-nonlinear blind source separation using neural networks with sandwiched structure,” Lecture Notes in Computer Science, Springer-Verlag, 3497:478-483, 2005(International Symposium on Neural Network, Chongqing, May 30-June 1, China).
    3. Fei Han, D.S.Huang, Yiu-Ming Cheung, and Guang-Bin Huang,“A new modified hybrid learning algorithm for feedforward neural networks,” Lecture Notes in Computer Science, Springer-Verlag, 3496:572-577, 2005(International Symposium on Neural Network, Chongqing, May 30-June 1, China).
    4. Ji-Xiang Du, D.S.Huang,Xia-Feng Wang, Lin Guo, “Shape recognition based on RBPNN and application to plant species identification,” Lecture Notes in Computer Science, Springer-Verlag, 3497:281-285, 2005 (International Symposium on Neural Network, Chongqing, May 30-June 1, China).

     

    2004

    1. Wen-Bo Zhao, M.Y. Zhang, L.M.Wang, J.Y. Du and D.S.Huang,“Multiple classifiers fusion system based on the radial basis probabilistic neural networks,”Lecture Notes in Computer Science, 3177: 314-319, Springer-Verlag, 2004(Fifth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), August 25-27, 2004, Exeter, UK).
    2. Xing-Ming Zhao, D.S.Huang, Y.M Cheung, Hong-Qiang Wang and Xin Huang,“A novel hybrid GA/SVM system for protein sequences classification,”Lecture Notes in Computer Science, 3177: 11-16, Springer-Verlag, 2004 (Fifth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), August 25-27, 2004, Exeter, UK).
    3. Zhi-Gang Zeng, D.S.Huangand Zeng-Fu Wang, “Global convergence of steepest descent for quadratic functions,” Lecture Notes in Computer Science 3177: 672-677, Springer-Verlag, 2004(Fifth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), August 25-27, 2004, Exeter, UK).
    4. Guang-Zheng Zhang and D.S.Huang, “Binary input encoding strategy based neural network for globulin protein inter-residue contacts map prediction,”Lecture Notes in Computer Science 3174: 513-518, Springer-Verlag, 2004 (International Symposium on Neural Network, Dalian, Aug.19-21, China).
    5. Bing-Yu Sun and D.S.Huang, “Support vector machine committee for classification,”Lecture Notes in Computer Science 3173: 648-653, Springer-Verlag, 2004 (International Symposium on Neural Network, Dalian, Aug.19-21, China).
    6. Hong-Qiang Wangand D.S.Huang, “A novel clustering analysis based on PCA and SOMs for gene expression patterns,” Lecture Notes in Computer Science 3174: 476-481, Springer-Verlag, 2004 (International Symposium on Neural Network, Dalian, Aug.19-21, China).
    7. Zhan-Li Sun and D.S.Huang,“Extracting target information in multispectral image using a modified KPCA approach,” Lecture Notes in Computer Science 3173: 774-779, Springer-Verlag, 2004 (International Symposium on Neural Network, Dalian, Aug.19-21, China).
    8. Zhi-Gang Zeng, D.S.Huangand Zeng-Fu Wang,“Pattern recognition based on stability of discrete-time cellular neural networks,” Lecture Notes in Computer Science 3173: 1008-1014, Springer-Verlag, 2004 (International Symposium on Neural Network, Dalian, Aug.19-21, China).
    9. Zhi-Gang Zeng, D.S.Huangand Zeng-Fu Wang,“Stability analysis of discrete-time cellular neural network,” Lecture Notes in Computer Science 3173:114-119, Springer-Verlag, 2004 (International Symposium on Neural Network, Dalian, Aug.19-21, China).

     

    2003

    1. D.S.Huangand Horace H.S.Ip, “On the choices of the parameters in general constrained learning algorithms,”Lecture Notes in Computer Science 2690: pp.967-974, Springer-Verlag, 2003 (Fourth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), March 21-23, 2003, Hong Kong).
    2. D.S.Huang“On the comparisons between RLSA and CLA for solving arbitrary linear simultaneous equations,” Lecture Notes in Computer Science 2690: pp.169-176, Springer-Verlag, 2003 (Fourth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), March 21-23, 2003, Hong Kong).
    3. Wenbo Zhao and D.S.Huang, “Comparative study between radial basis probabilistic neural networks and radial basis function neural networks,” Lecture Notes in Computer Science 2690: pp.389-396, Springer-Verlag, 2003 (Fourth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), March 21-23, 2003, Hong Kong).

     

  • International Conference Papers

    •  

    2019

    1. Jiangchuan Wei, Hanli Wang, Yun Yi, Qinyu Li, and D.S.Huang, “P3D-CTN: Pseudo-3D convolutional tube network for spatio-temporal action detection in videos,” 2019 IEEE International Conference on Image Processing (ICIP’19), Taipei, Taiwan,  pp. 300-304, Sept. 22-25,  2019.
    2. Yihao Chen, Hanli Wang, Qinyu Li, and D.S.Huang, “Data driven regularization for convolutional neural networks on image classification,” 2019 IEEE International Symposium on Circuits and Systems (ISCAS'19), Sapporo, Japan, pp. 1-5, May 26-29, 2019.

     

    2018

    1. Basma Abdulaimma, Abir Hussain, Paul Fergus, Dhiya Al-Jumeily, Paulo Lisboa, D.S.Huang, Naeem Radi, “Improving type 2 diabetes phenotypic classification by combining genetics and conventional risk factors,” IEEE Congress on Evolutionary Computation, Rio de Janeiro, Brazil, 531-537, July 8-13, 2018

     

    2017

    1. Dayuan Li, Lin Zhu, Wenzheng Bao, Fei Cheng, Yi Ren and D.S.Huang, "Cross-validated smooth multi-instance learning", 2017 International Conference on Neural Networks (IJCNN2017), Alaska, USA, May 14–19, 2017, pp.321-1325, 2017.
    2. Chong-Ya Li, Lin Zhu, Wen-Zheng Bao, Yong-Li Jiang, Chang-An Yuan and D.S.Huang, “Convex local sensitive low rank matrix approximation,” 2017 International Joint Conference on Neural Networks (IJCNN 2017), Alaska, USA, May 14–19, 2017, pp.256-261, 2017.

     

    2016

    1. Qing-Yi Liu, Lin Zhu, and D.S.Huang, “Visual data completion via local sensitive low rank tensor learning,” 2016 IEEE World Congress on Computational Intelligence (WCCI)-International Conference on Neural Networks (IJCNN2016), Vancouver, Canada, 24-29 July 2016, 2016.
    2. Gang Wang, D.S.Huang,“Representing logical relations automatically by probabilistic logical dynamical neural network,” 2016 IEEE World Congress on Computational Intelligence (WCCI)-International Conference on Neural Networks (IJCNN2016), Vancouver, Canada, 24-29 July 2016, 2016.

     

    2015

    1. Hongbo Zhang, Lin Zhu, and D.S.Huang, "DiscMLA: AUC-based discriminative motif learning," 2015 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2015), November 9-12, 2015, Washington D.C., USA, pp.250-255.
    2. Lin Zhu, Wei-Li Guo, D.S.Huang, and Can-Yi Lu, "Imputation of ChIP-seq datasets via Low Rank Convex Co-Embedding," in Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on, 2015, pp. 141-144.

     

    2014

    1. Jing-Hua Yuan, Yong Gan and D.S.Huang,“Completed hybrid local binary pattern for texture classification,” 2014 IEEE World Congress on Computational Intelligence (WCCI)-International Conference on Neural Networks (IJCNN2014), Beijing, China, July 6-11, 2014.

     

    2013

     

    1. Suping Deng, Jinghua Yuan, D.S.Huang, Zhen Wang, “SFAPS: an R package for structure/function analysis of protein sequences based on informational spectrum method, “2013 IEEE International Conference on Bioinformatics and Biomedicine, Shanghai, China, Dec. 18-21, 2013, 29-34, 2013.

     

    2012

    1. Lin Zhu and D.S.Huang, “A scalable rayleigh-ritz style method for large scale Canonical Correlation Analysis,” 2012 IEEE World Congress on Computational Intelligence (WCCI)-International Conference on Neural Networks (IJCNN2012), Brisbane, Australia, June, 10-15, 2012, pp., 2012.

     

    2010

     

    1. Shanwen Zhang, Yingke Lei and D.S.Huang, “Two-dimensional neighborhoodhood discriminant projection,” 2010 IEEE World Congress on Computational Intelligence (WCCI)-International Conference on Neural Networks (IJCNN2010), Barcelona, Spain, July 18-23, pp., 2010.
    2. Lei Tang, Ying-Ke Lei, Lin Zhu and D.S.Huang, “Dimensionality reduction based on minimax risk criterion for face recognition,” IEEE World Congress on Computational Intelligence, Barcelona Spain. pp:1-6, July 18-23, 2010.
    3. Ying-Ke Lei, Rong-Xiang Hu, Shan-Wen Zhang, and De-Shuang Huang, “Orthogonal linear local spline discriminant embedding for face recognition,” 2010 International Joint Conference on Neural Networks (IJCNN 2010), Barcelona, Spain, July 18-23, 2010, pp: 3225-3232.

     

    2009

     

    1. Wei Jia, Yi-Hai Zhu, Ling-Feng Liu, D.S.Huang, “Fast palmprint retrieval using principal lines”, Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX, USA, October 2009, pp: 4118-4123.
    2. Marcos Quiles, DeLiang Wang, Liang Zhao, Roseli Romero and D.S.Huang, “An oscillatory correlation model of object-based attention,” The 2007 International Joint Conference on Neural Networks (IJCNN), Atlanta, Georgia, USA, June 14-19, 2009.
    3. Chun-Gui Xu, D.S.Huang, "The analysis of microarray datasets using a genetic programming,” the 2009 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2009), Nashvile, TN, USA, March 30-April 2, 2009.

     

    2008

     

    1. Jie Gui, D.S.Huang, and Zhuhong You, “An improvement on learning with local and global consistency,” 2008 The 19thInternational Conference on Pattern Recognition (ICPRI2008), Tampa, Florida, USA, December 8-11, 2008, pp.1-4.
    2. Wei Jia, D.S.Huang, Dacheng Tao, David Zhang, “Palmprint identification based on directional representation,” 2008 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2008), Singapore, 12-15 October 2008, pp. 1562-1567.
    3. Bo Li, D.S.Huang, Chao Wang, “Improving the robustness of ISOMAP by de-noising,” Proceedings of 2008 IEEE World Congress on Computational Intelligence (WCCI 2008), Hong Kong, June 1-6, 2008, pp.266-270.
    4. Bo Li, D.S.Huang, and Kun-Hong Liu, “Constrained maximum variance mapping ,” Proceedings of 2008 IEEE World Congress on Computational Intelligence (WCCI 2008), Hong Kong , June 1-6, 2008, pp.535-538.
    5. Huan Xu, D.S.Huang, “One class support vector machine for distinguishing photographs and graphics,” The 2008 IEEE International Conference on Networking, Sensing and Control, SanyaChina, Vol.I, pp. 602-607, April 6-8, 2008.
    6. D.S.Huang, “Density-based clustering using level set method,” The 2ndKES International Symposium on Agent and Multi-Agent Systems: technologies and Applications, March 27-28, 2008, Incheon Korea.

     

    2007

    1. Kun-Hong Liu, D.S.Huang, and Jun Zhang,“Microarray data prediction by evolutionary classifier ensemble system,” The 2007 IEEE Congress on Evolutionary Computation (CEC), Singapore, September 25-28, 2007, pp.634-637.
    2. Kun-Hong Liu, D.S.Huang, and Bo Li, “Improving the performance of ICA based microarray data prediction model with genetic algorithm,” The 2007 IEEE Congress on Evolutionary Computation (CEC), Singapore, September 25-28, 2007, pp. 606 - 611.
    3. Jun Zhang, D.S.Huangand Kun-Hong Liu, “Multi-sub-swarm particle swarm optimization algorithm for multimodal function optimization,” The 2007 IEEE Congress on Evolutionary Computation (CEC), Singapore, September 25-28, 2007, pp.3215-3220.
    4. Zhong-Qiu Zhao and D.S.Huang, "An evolutionary modular neural network for unbalanced pattern classifications," The 2007 IEEE Congress on Evolutionary Computation (CEC), Singapore, September 25-28, 2007,pp.1662-1669.
    5. D.S.Huang, “Protein contact map prediction using evolutionary optimization technique,” The Second International Conference on Bio-Inspired Computing: Theory and Applications (BIC-TA 2007), Zhenzhou, China, Sept. 15-18, 2007.
    6. Zhong-Hua Quan, D.S.Huang, Kun-Hong Liu, and Kwok-Wing Chau, “A hybrid HMM/ANN based approach for online signature verification”, The 2007 International Joint Conference on Neural Networks (IJCNN), Orlando, Florida, USA, August 12-17, 2007, pp. 402 - 405.
    7. Guo-Zhu Wen, Xiao-Yong Guo, D.S.Huang, and Kun-Hong Liu, “Application of self-organizing map in aerosol single particles data clustering”, The 2007 International Joint Conference on Neural Networks (IJCNN), Orlando, Florida, USA, August 12-17, 2007, pp. 991 - 996.
    8. Jun-Feng Xia, Bing Wang and D.S.Huang, “Inferring strengths of protein-protein interaction using artificial neural network,” The 2007 International Joint Conference on Neural Networks (IJCNN), Orlando, Florida, USA, August 12-17, 2007,pp.2471– 2475.
    9. Wei Jia, D.S.Huang, “Palmprint verification based on line orientation code,” The 2007 International Joint Conference on Neural Networks (IJCNN), Orlando, Florida, USA, August 12-17, 2007, pp.2510-2514.
    10. Peng Chen, Bing Wang, Hau-San Wong and D.S.Huang, “Prediction of long-range contacts from sequence profile,” The 2007 International Joint Conference on Neural Networks (IJCNN), Orlando, Florida, USA, August 12-17, 2007, pp.938-943.
    11. Bing Wang, Lu Sheng Ge, D.S.Huang, Hau San Wong, “Prediction of protein-protein interacting sites by combining SVM algorithm with Bayesian method,” Third International Conference on Natural Computation, ICNC 2007, v 2, Proceedings, 2007, p p.329-333.

     

    2006

    1. Zhi-Kai Huang,D.S.Huang, Michael R Lyu; Tat-Ming Lok, “Classification based on Gabor filter using RBPNN classification,” 2006 International Conference on Computational Intelligence and Security, Proceedings, 759-762, 2006.
    2. Zhi-Kai Huang,D.S.Huang, Zhong-Hua Quan, “Bark classification using RBPNN based on Gabor filter in different color space,” IEEE International Conference on Information Acquisition, Vols.1 and 2, 946-950, 2006.
    3. Zhong-Hua Quan, D.S.Huang, Xiao-Lei Xia, Michael R. Lyu, Tat-Ming Lok, “Spectrum analysis based on windows with variable widths for online signature verification,” International Conference on Pattern Recognition (ICPR), Hong Kong, vol. 2, 20-24 Aug. 2006, pp.1122-1125.
    4. Bing Wang, Hau San Wong, Peng Chen, Hong-Qiang Wang and D.S.Huang, “Predicting protein-protein interaction sites using radial basis function neural networks,” The 2006 International Joint Conference on Neural Networks (IJCNN2006), Sheraton Vancouver Wall Centre, Vancouver, BC, Canada, 16-21 July 2006, pp.2325–2330.
    5. Peng Chen; Bing Wang; Hau-San Wong; D.S.Huang, “Long-Range Interaction Analysis using Principal Component Analysis,” The 2006 International Joint Conference on Neural Networks (IJCNN2006), Sheraton Vancouver Wall Centre, Vancouver, BC, Canada, 16-21 July 2006, pp.2331– 2336.

     

    2005

    1. Ji-Xiang Du, D.S.Huang, Xiao-Feng Wang and Xiao Gu, “Neural network-based shape recognition using generalized differential evolution training algorithm,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.4, 31 July-4 Aug. 2005. pp.2012-2017.
    2. Jing-Jing Li, D.S.Huang, Robert MacCallum and Xiao-Run Wu, “Characterizing human gene splice sites using evolved regular expressions,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.1, 31 July-4 Aug. 2005, pp.493-498.
    3. Li Shang, D.S.Huang, Chun-Hou Zheng and Zhan-Li Sun, “Natural image compression using an extended non-negative sparse coding neural network technique,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.3, July 31-Aug. 4, 2005, pp.1866-1871.
    4. Peng Chen, D.S.Huang, Bing Wang, Yunping Zhu and Yixue Li, “Prediction of contact map integrated PNN with conformational energy,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.1, 31 July-4 Aug. 2005. pp. 499-502.
    5. Zhan-Li Sun, D.S.Huang, Chun-Hou Zheng and Li Shang, “Blind inversion of Wiener system for single source,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol. 2, 31 July-4 Aug. 2005, pp.1235-1238.
    6. Jun-Hua Han, D. S. Huang, Tat-Ming Lok, and Michael R. Lyu, “A novel image retrieval system based on BP neural network,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.4, 31 July-4 Aug. 2005, pp.2561-2564.
    7. Bing Wang, D.S.Huang, Peng Chen, Yunping Zhu and Yixue Li, “Predicting Protein-Protein Interactions Based on Protein-Domain Relationships,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.1, 31 July-4 Aug. 2005. pp.316-319.
    8. Ji-Xiang Du,D.S.Huang, Jun Zhang, Xiao-Feng Wang, “Shape matching using fuzzy discrete particle swarm optimization,” Proceedings 2005 IEEE International Conference on Swarm Intelligence Symposium, June 8-10, 2005, pp.415-418, 2005.
    9. Xing-Ming Zhao; Yiu-Ming Cheung; D.S.Huang, “Microarray data analysis using rival penalized EM algorithm in normal mixture models,”2005 Proceedings of 2005 IEEE International Workshop on VLSI Design and Video Technology, 28-30 May 2005, pp.129-132.
    10. Li Shang, D.S.Huang, “Image denoising using non-negative sparse coding shrinkage algorithm,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005 (CVPR 2005). 20-26 June 2005, San Diego, CA, USA, Volume 1, pp. 1017-1022.
    11. Jun-Hua Han, D.S.Huang, “A novel BP –based image retrieval system,” The IEEE International Symposium on Circuits and Systems (ISCAS), Kobe, Japan, May 23-26, 2005, pp.1557-1560.

     

    2004

    1. Zhigang Zeng,Zengfu Wang, and D.S.Huang, “Global exponential stability of delayed Cohen-Grossberg neural networks,” The 8th International Conference on Control, Automation, Robotics and Vision (ICARCV2004), December 6-9, 2004, Kun Ming, China, pp.2253-2256.
    2. Jian-Xun Miand D.S.Huang, “Image compression using principal component neural network,” The 8th International Conference on Control, Automation, Robotics and Vision (ICARCV2004), December 6-9, 2004, Kun Ming, China, pp.698-701.
    3. Guo-Jun Zhang, Xiao-Feng Wang and D.S.Huang, Zheru Chi, Yiu-Ming Cheung, Ji-Xiang Du and Yuan-Yuan Wan, “A hypersphere method for plant leaves classification,” Proceedings of The 2004 International Symposium on Intelligent Multimedia, Video & Speech Processing (ISIMP 2004), October20-22, 2004, Hong Kong, China, pp.165-168.
    4. Yuan-Yuan Wan, Ji-Xiang Du, D.S.Huang, Zheru Chi, Yiu-Ming Cheung, Xiao-Feng Wang, Guo-Jun Zhang, “Bark texture feature extraction based on statistical texture analysis,” Proceedings of The 2004 International Symposium on Intelligent Multimedia, Video & Speech Processing (ISIMP 2004), October20-22, 2004, Hong Kong, China, pp.482-485.
    5. Zhigang Zengand D.S.Huang, "Pattern memory and acquisition based on stability of cellular neural networks," The 2004 International Joint Conference on Neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp.943-947.
    6. Guang-Zheng Zhangand D.S.Huang, "Aligning multiple protein sequence by an improved genetic algorithm," The 2004 International Joint Conference on neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp. 1179-1183.
    7. Guang-Zheng Zhangand D.S.Huang, "Combing Genetic Algorithm with Neural Network Technique for Protein Inter-Residue Spatial Distance Prediction," The 2004 International Joint Conference on Neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp.1687-1691.
    8. Bing-Yu Sunand D.S.Huang, "Least squares support vector machine ensemble," The 2004 International Joint Conference on Neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp. 2013-2016.
    9. Jun-Hua Han, D.S.Huang, Zhan-Li Sun and Yiu-Ming Cheung, "A novel mixed pixels unmixing method for multispectral images," The 2004 International Joint Conference on Neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp.2541-2545.
    10. Zhong-Qiu Zhao, D.S.Huangand Lin Guo, "A novel clustering-neural tree for pattern classification," The 2004 International Joint Conference on Neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp.1303-1308.
    11. Xin Huang, D.S.Huang, Hong-Qiang Wang and Xing-Ming Zhao, "Representation of DNA sequences with multiple resolutions and BP neural network based classification," The 2004 International Joint Conference on Neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp.1185-1189.
    12. Hong-Qiang Wang, D.S.Huang, Guang-Zheng Zhang and Xing-Ming Zhao, "A feature_core and SVM-based algorithm for identification of bioprocess-specific genome features," The 2004 International Joint Conference on Neural Networks (IJCNN2004), Budapest Hungary, July 25-29, 2004, pp.1675-1679.
    13. Guang-Zheng Zhangand D.S.Huang, "Radial basis function neural network optimized by GA for soybean protein sequence residue spatial distance prediction", 2004 IEEE Congress on Evolutionary Computation, Portland, Oregon, USA, vol.1, June 19-23, 2004,pp.1015–1019.
    14. Zhi-Gang Zeng, D.S.Huangand Zengfu Wang, “Practical stability criteria for cellular neural networks described by a template,” The 5th World Congress on Intelligent Control and Automation (WCICA04), June 14-18, 2004, Hangzhou, China, pp.160-162.
    15. Hai-Tao Fangand D.S.Huang, “Wavelet de-noising by means of trimmed thresholding,” The 5th World Congress on Intelligent Control and Automation (WCICA04), June 14-18, 2004, Hangzhou, China, pp.1621-1624.
    16. Bing-Yu Sunand D.S.Huang, “Texture classification based on support vector machine and wavelet transform,” The 5th World Congress on Intelligent Control and Automation (WCICA04), June 14-18, 2004, Hangzhou, China, pp.1862-1864.
    17. Zhong-Qiu Zhao, D.S.Huangand Bin-Yu Sun, “Human facial recognition based on multiple feature domains,” The 5th World Congress on Intelligent Control and Automation (WCICA04), June 14-18, 2004, Hangzhou, China, pp.4150-4155.
    18. D.S.Huangand Guang-Zheng Zhang, “Protein secondary structure prediction by intelligent computing technique,” New Horizons in the Post Genomics Era, May 21-22, 2004, Beijing.
    19. Guang-Zheng Zhang, D.S.Huangand Hong-Qiang Wang, “Protein secondary structure prediction based on the amino acids conformational classification and neural network technique,” The 2004 Int. Conf on Acoustics, Speech, and Signal Processing (ICASSP), Montreal, Quebec, Canada, pp. V-573-576, May 17-21, 2004.

     

    2003

    1. Bing-Yu Sun, D.S.Huang, “Support vector clustering for multiclass classification problems,”The Congress on Evolutionary Computation, Canberra, Australia, 8th - 12th December 2003, pp.1480-1485.
    2. D.S.Huang, “The further discussions on constrained learning algorithms,” 2003 Int. Joint Conf on Neural Networks (IJCNN), Portland, Oregon, July 20-24, 2003,pp.1868-1872.
    3. D.S.Huang, Horace H.S.Ip, Law Ken C.K. and H.S.Wong, “Finding the ordered roots of arbitrary polynomials using constrained partitioning neural networks,” 2003 Int. Joint Conf on Neural Networks (IJCNN), Portland, Oregon, July 20-24, 2003, pp.1098-1103.
    4. D.S.Huangand Horace H.S.Ip, “Finding the maximum modulus roots of polynomials based on constrained neural networks,” The 2003 Int. Conf on Acoustics, Speech, and Signal Processing (ICASSP), Hong Kong, April 6-10, 2003, Vol.II, pp.797-800.
    5. Wenbo Zhao, D.S.Huangand Lin Guo,“ Optimizing radial basis probabilistic neural networks using recursive orthogonal least squares algorithms combined with micro-genetic algorithms,” 2003 Int. Joint Conf. on Neural Networks (IJCNN), Portland, Oregon, July 20-24, 2003,pp.2277-2282.
    6. Lin Guo, D.S.Huangand Wenbo Zhao, “The optimization of radial basis probabilistic neural networks based on genetic algorithms,” Int. Joint Conf. on Neural Networks (IJCNN2003), Portland, Oregon, July 20-24, 2003, pp.3213-3217.
    7. Lin Guo andD.S.Huang , “Human face recognition based on Radial basis probabilistic neural network,” Int. Joint Conf on Neural Networks (IJCNN2003), Portland, Oregon, July 20-24, 2003,pp.2208-2211.

     

    2002

    1. D.S.Huang, “Constrained learning algorithms for finding the roots of polynomials: A case study,” IEEE Region 10 Technical Conf on Computers, Communications, Control and Power Engineering, Vol.III, Beijing, China, Oct. 28-31, 2002, pp.1516-1520.
    2. D.S.Huang, “A recursive root moment method for finding roots of polynomials based on neural constrained learning method,” IEEE Region 10 Technical Conf on Computers, Communications, Control and Power Engineering, Vol.I, Beijing, China, Oct. 28-31, 2002, pp.703-707.
    3. D.S.Huang, Xiaofeng Wang and Haiyin Hu, “On the comparisons between two outer-supervised learning algorithms for finding the inversion of arbitrary nonsingular matrices,” The 6thInt. Conf on Signal Processing (ICSP02) Proceeding, Beijing, China, Aug. 26-30, 2002, pp. 1705-1710.
    4. D.S.Huangand Wenbo Zhao, “A comprehensive understanding for radial basis probabilistic neural networks,” The 6th Int. Conf on Signal Processing (ICSP02) Proceeding, Beijing, China, Aug. 26-30, 2002, pp. 1237-1242.
    5. D.S.Huangand Wenbo Zhao, “A novel method for improving the classification capability of radial basis probabilistic neural network classifiers,” World Congress on Computational Intelligence (WCCI-IJCNN2002), Hilton Hawaiian Village Hotel, Honolulu, Hawaii, May 12-17, 2002, pp.102-106.
    6. Wenbo Zhao and D.S.Huang, “The structure optimization of radial basis probabilistic neural networks based on genetic algorithms,” The 2002 IEEE World Congress on Computational Intelligence, IJCNN02, Hilton Hawalian Village Hotel, Honolulu, Hawaii, May 12-17, 2002, pp.1086-1091.
    7. Wenbo Zhao, D.S.Huangand Yunjian Ge, “Application of genetic algorithms to the structure optimization of radial basis probabilistic neural networks,” The 6th Conf on Signal Processing (ICSP02) Proceeding, Beijing, China, Aug. 26-30, 2002, pp. 1243-1246.
    8. Wenbo Zhao and D.S.Huang, “Application of recursive orthogonal least squares algorithm to the structure optimization of radial basis probabilistic neural networks,” The 6thInt. Conf on Signal Processing (ICSP02) Proceeding, Beijing, China, Aug. 26-30, 2002, pp. 1211-1214.

     

    2001

    1. D.S.Huang, “Revisit to constrained learning algorithm,” The 8thInt. Conf on Neural Information Processing (ICONIP), Shanghai, China, Vol. I, pp.459-464, Nov. 14-18, 2001.
    2. D.S.Huang, “The dilatation method for the close roots of polynomials,” The 8thInt. Conf on Neural Information Processing (ICONIP), Shanghai, China, Vol. II, pp.1083-1087, Nov. 14-18, 2001.
    3. D.S.Huang, “Finding roots of polynomials based on root moments,” The 8thInt. Conf on Neural Information Processing (ICONIP), Shanghai, China, Vol. III, pp.1565-1571, Nov. 14-18, 2001.
    4. D.S.Huang, “The structure optimization of radial basis probabilistic neural networks based on orthogonal least square,” The Second Int. Symposium on Intelligent and Complex Systems, Wuhan, Three Gorges, China, Oct. 17-20, 2001, p.45.
    5. D.S.Huang, “Using a fast recursive root moment constraint relation combing with neural networks for finding roots of arbitrary polynomials,” The Second Int. Symposium on Intelligent and Complex Systems, Wuhan, Three Gorges, China, Oct. 17-20, 2001, p.46.
    6. D.S.Huangand Zheru Chi, “Neural networks with problem decomposition for finding real roots of polynomials,” 2001 Int. Joint Conf. On Neural Networks (IJCNN2001), Washington, DC, Vol. Addendum, pp.25-30, July 15-19, 2001.
    7. D.S.Huangand Zheru Chi, “Solving linear simultaneous equations by constraining learning neural networks,” 2001 Int. Joint Conf. On Neural Networks (IJCNN2001), Washington, DC, Vol. Addendum, pp.31-26, July 15-19, 2001.
    8. D.S.Huangand Zheru Chi, “Finding complex roots of polynomials by feedforward neural networks,” 2001 Int. Joint Conf. On Neural Networks (IJCNN2001), Washington, DC, Vol. Addendum, pp.13-18, July 15-19, 2001.
    9. D.S.Huangand Zheru Chi, “Constraining learning linear neural networks for inverting of complex matrices,” 2001 Int. Joint Conf. On Neural Networks (IJCNN2001), Washington, DC, Vol. Addendum, pp.7-12, July 15-19, 2001.
    10. Song Liangtu, D.S.Huang, Wang Rujing and Li Yan, “The implementation of uncertainty reasoning based on web and database technology,” Int. Conf on Agricultural Science & Technology: Promoting Global Innovation of Agricultural Science & Technology & Sustainable Agriculture Development, Session 6: Information Technology of Agriculture, Nov. 7-9, 2001, Beijing, 76-80.
    11. Xiao-Feng Wang, Wang Rujing and D.S.Huang, “Integrative technique research of GIS & agriculture intelligent decision support system,” Int. Conf. on Agricultural Science & Technology: Promoting Global Innovation of Agricultural Science & Technology & Sustainable Agriculture Development, Session 6: Information Technology of Agriculture, Nov. 7-9, 2001, Beijing, 233-236.
    12. Wang Rujing, D.S.Huangand Song Liangtu, “Study on storage structure and the management system of knowledge base in aids,” Int. Conf on Agricultural Science & Technology: Promoting Global Innovation of Agricultural Science & Technology & Sustainable Agriculture Development, Session 6: Information Technology of Agriculture, Nov. 7-9, 2001, Beijing, 508-513.

     

    2000

    1. D.S.Huang,“A neural network based factorization model for polynomials in several elements,”2000 5th Int. Conf on Signal Processing Proceedings (WCC-ICSP2000), Aug. 21-25, 2000, Beijing China, pp.1617-1622(ISTP, INSPEC).
    2. D.S.Huang,“Application of neural networks to finding real roots of polynomials in one element,”The 7th Int. Conf on Neural Information Processing (ICONIP2000) Proceedings, Taejon, Korea, Nov.14-17, 2000, Vol.II, pp.1108-1113.

     

    1999

    1. D.S.Huang,“A fusion design of linear-nonlinear feedforward neural networks for pattern classification,”1999 Int. Joint Conf. On Neural Networks (IJCNN1999), Washington, DC, July 10-16,1999, pp.2768-2771.
    2. D.S.Huang,“On the conditions of outer-supervised feedforward neural networks for null cost learning,”1999 Int. Joint Conf. On Neural Networks (IJCNN1999), Washington, DC, July 10-16,1999, pp.841-845.
    3. D.S.Huang,“Classification properties and classification mechanism of feedforward neural network classifiers,”SPIE Sensor Fusion: Architecture, Algorithm, and Applications Ⅲ, Orlando, FL: pp.442-447, April 5-9, 1999.
    4. D.S.Huang,“Neural pattern analyses based on a novel error cost function,”Proceedings of the Int. Conf. on Parallel and Distributed Processing Techniques and Applications (PDPTA’99), Las Vegas, Nevada, CSREA Press, USA, Vol. VI, June 28-July 1,1999, pp.2875-2880.
    5. D.S.Huang,“A novel minimal norm based learning subspace method,”Proceedings of the 2th Int. Conf. on Information Fusion (FUSION’99), Sunnyvale Hilton Inn, Sunnyvale, California, USA, July 6-8,1999, pp.1102-1106.
    6. Z.Liang, X.G.He and D.S.Huang,“Gradient-Newton learning algorithm for feedforward neural networks,”Proceedings of the Int. Conf. on Parallel and Distributed Processing Techniques and Applications (PDPTA’99), Las Vegas, Nevada, CSREA Press, USA, Vol.VI, June 28-July 1,1999, pp.2870-2874.

     

    1998

    1. D.S.Huang,“A novel forward-backward smoothing based learning subspace method,”1998 IEEE World Congress on Computational Intelligence (WCCI-IJCNN1998), Anchorage, Alaska, Proceedings, Vol.Ⅱ, pp.1113-1118, May 4-9,1998.
    2. D.S.Huang,“On the solutions of one-class-one-outputed feedforward neural network classifiers using backpropagation training,”The 4th Int. Conf. On Signal Processing (ICSP98) Proceedings, Publishing House of Electronics Industry, Oct. 12-16, 1998, Beijing, China, pp.1301-1305.
    3. D.S.Huang,“Linear feedforward neural network classifiers and reduced-rank approximation,”The 4th Int. Conf. On Signal Processing (ICSP98) Proceedings, Publishing House of Electronics Industry, Oct. 12-16, 1998, Beijing, China, pp.1331-1334.
    4. D.S.Huang,“An analysis of structure properties for feedforward neural networks,”The Int. Conf. on Neural Networks and Brain Proceedings, Publishing House of Electronics Industry, Oct. 27-30, 1998,Beijing, China, pp.463-466.
    5. D.S.Huang,“A new definition of error cost function for layered feedforward networks,”The Int. Conf. on Neural Networks and Brain Proceedings, Publishing House of Electronics Industry, Oct. 27-30, 1998,Beijing, China, pp.467-470.

     

    1997

    1. D.S.Huangand D.P.Zhu,“A method for discriminating radar clutter sequences from target range images,”Proceedings of Int. Conf on Imaging Science, Systems, and Technology, June 30-July 3, 1997,Las Vegas, Nevada, USA, pp.183-188.

     

    1996

    1. D.S.Huangand S.D.Ma,“A new radial basis probabilistic neural network model,”The 3rd Int. Conf on Signal Processing (ICSP) Proceedings, Oct 14～18, 1996, Beijing, China, pp.1449-1452.
    2. D.S.Huangand S.D.Ma,“Fisher linear discrimination in the linear feedforward network classifiers,”Int. Conf on Robot, Optimization, Vision, Parallel Industry Automation (ROVPIA96), Nov. 28～30, 1996, Ipoh, Malaysia, pp.662-667.
    3. D.S.Huang,“One-layer linear perceptron for the inversion of nonsingular matrix,”Int. Conf on Robot, Optimization, Vision, Parallel Industry Automation (ROVPIA96), Nov. 28～30, 1996, Ipoh, Malaysia, pp.639-643.
    4. D.S.Huang,“The attractor and basin of attraction in the feedforward network classifiers,”Int. Conf on Robot, Optimization, Vision, Parallel Industry Automation (ROVPIA96), Nov. 28～30, 1996, Ipoh, Malaysia, pp.656-661.
    5. D.S.Huang,“The generalization capability of self-supervised learning subspace method for pattern recognition,”Int. Conf on Robot, Optimization, Vision, Parallel Industry Automation (ROVPIA96), Nov. 28～30, 1996, Ipoh, Malaysia, pp.907-911.
    6. D.S.Huang,“The decorrelation properties of the hidden layer in the nonlinear feedforward networks,”Int. Conf on Robot, Optimization, Vision, Parallel Industry Automation (ROVPIA96), Nov. 28～30, 1996, Ipoh, Malaysia, pp.644-649.

    1995

    1. D.S.Huang, E.K.Mao and Y.Q.Han,“Application of function link net to recognition of radar targets,”ICASSP’95, Detroit, Michigan, USA, Vol.V, pp.3487-3490,1995.

     

    1994

    1. D.S.Huang, X.X.Lv and K.P.Yuan,“A study of backpropagation learning algorithm of multilayer percetron networks based on recursive least squares,”Proc. of the Sixth Japan-China International Conference on Computer Applications,Sept. 16-18,1994,Sapporo,Japan, pp.169-172(J-4).

     

    1992

    1. D.S.Huangand Z.Bao,“The improved learning subspace method for the recognition of objects-ships & chaff,”Int. Joint Conf on Neural Networks (IJCNN92), Oct., 1992,Beijing.
    2. D.S.Huangand Z.Bao,“The forward and backward smoothing learning subspace method for pattern recognition,”IC of AMSE on MSC’92,Nev., 1992, Hefei.

     

    1990

    1. D.S.Huangand D.J.Zhu：“The study of adaptive spectrum estimation to frequency hopping signal,”The First Int. Conf on Signal Processing (ICSP90), Oct., 1990, Beijing,pp.325-328.  

     

     

     

    2006

    1. D.S.Huang, “A survey and prospect for swarm optimization algorithms,” 2006 National Conference on Chart Theory and System Optimization, 15-17 October, 2006, Xi’an, China (Plenary Talk).

     

    1. D.S.Huang, “Constrained learning algorithms: Current status, prospects and problems,” The 12thNational Youth Conf of Chinese Institute of Electronics (CIE-YC’2006), Sep. 25-29, 2005,Xi’an, China (Plenary Talk).

     

    2005

     

    1. D.S.Huang, “Microarray data analysis for gene selection and cancer classification,” The 11thNational Youth Conf of Chinese Institute of Electronics (CIE-YC’2005), Sep. 24-26, 2005,Shandong, China (Plenary Talk).

     

    1. D.S.Huang, “Long-range interaction analysis of protein residues based on principal component analysis and boltzmann theory,” The 3rd national Conference on Proteomics, July 25-27,2005, Changchun, China (Invited Session Talk).

     

     

     

    2004

     

    1. D.S.Huang, "Machine learning and bioinformatics," The 3rd Forum on Frontier and Cross-Science of Postdoctors of Chinese Academy of Sciences, Dec., 6,2004, Beijing (Invited Plenary Talk).
    2. D.S.Huang, “The technique of protein structure prediction based on machine learning theory,” The 10thNational Youth Conf of Chinese Institute of Electronics (CIE-YC’2004), Sep. 23-26, 2004,Beijing, China (Plenary Talk).

     

    2003

     

    1. D.S.Huang, “On the state-of-the-art of bioinformatics researches,” The 9thNational Youth Conf of Chinese Institute of Electronics (CIE-YC’2003), August 2003,Hangzhou, Zhejiang (Plenary Talk).
    2. Guang-Zheng Zhang and D.S.Huang, “Protein secondary structure prediction based on amino acid conformational preferenceand neural networks technique,” The 81th Young Scientist Forum of China Association for Science and Technology with the Theme “Bioinformatics and Evolutionary Computation”, Nov. 28-29, 2003, Beijing, China.
    3. Zhi-Gang Zeng, Xiaoxin Liao and D.S.Huang, “Global exponential stability of cellular neural networks with input vector,” 2003 Chinese Intelligent Automation Conference (CIAC’2003) Proceedings, Hong Kong, China, Dec. 15-17, 2003, pp.141-145.
    4. Guang-Zheng Zhang and D.S.Huang, “Using neural networks to predict secondary structure by integration of amino acid conformational preference and multiple sequence alignment,” 2003 Chinese Intelligent Automation Conference (CIAC’2003) Proceedings,Hong Kong, China, Dec. 15-17, 2003, pp.149-154.
    5. Zhong-Qiu Zhao, D.S.Huangand Lin Guo, “Human facial recognition based on radial basis function neural networks committee,” 2003 Chinese Intelligent Automation Conference (CIAC’2003) Proceedings, Hong Kong, China, Dec. 15-17, 2003, pp.509-515.
    6. Zhong-Qiu Zhao and D.S.Huang, “A novel adaptive neural networks-tree classifier”, The Workshop on Information Acquisition of Chinese Academy of Sciences, Hefei, China, Nov. 24-26, 2003, pp.237-243.
    7. Bing-Yu Sun, D.S.Huangand Lin Guo, “Human face recognition using generalized kernel Fisher discriminant,” 2003 Chinese Intelligent Automation Conference (CIAC’2003) Proceedings, Hong Kong, China, Dec. 15-17, 2003, pp.466-472.
    8. Hai-Tao Fang and D.S.Huang, “Application of wavelet neural networks to Lidar signal de-noising,” 2003 Chinese Intelligent Automation Conference (CIAC’2003) Proceedings, Hong Kong, China, Dec. 15-17, 2003, pp.696-702.

     

    2002

     

    1. D.S.Huangand Horace H.S.Ip, “A talk on neural root finders,” The 14th National Conf on Neural Computation,2002.12.13-18,Beijing, pp.193-197 (Invited Speech).
    2. D.S.Huangand Horace H.S.Ip, “Dual extended Kalman filtering algorithm: theory and applications,” The 8th National Youth Conf of Chinese Institute of Electronics (CIE-YC’2002), Aug. 13-18, 2002,Hefei, Anhui,pp.13-16(Plenary Talk).
    3. Wenbo Zhao, D.S.Huang, Nansheng Kang and Benyu Sun,“On the comparative study between RBFN and RBPNN,”The 8th National Youth Conference of Chinese Institute of Electronics (CIE-YC’02), Hefei, Anhui, China. Aug. 13-18, 2002, pp.768-773.

     

    2001

     

    1. D.S.Huang,“The application and prospect of the Constrained learning algorithms encoded by the a priori information,”The 7thNational Youth Conf of Chinese Institute of Electronics (CIE-YC’2001), Publishing House of Beijing Institute of Broadcast, Aug. 17-20, 2001, WuNuMuQi, pp.6-12(Plenary Talk).

     

    1999

     

    1. D.S.Huang,“On the prospect of artificial intelligence and neural networks in 21th century,”The 5thNational Youth Conf. of Chinese Institute of Electronics (CIE-YC’99), Beijing, China, Dec. 1999, pp.1-6(Plenary Talk).
    2. D.S.Huang,“On the modular associative neural network classifiers,”The 5thNational United conf on Computer and Application, Vol.3,pp.7.285-7.290,Beijing, Dec. 1999.
    3. D.S.Huang,“Learning vector quantization based on Voronoi vectors and units,”The 5thNational Youth Conf. of Chinese Institute of Electronics (CIE-YC’99), Haerbing, China, Dec. 1999, pp.376-380.
    4. D.S.Huang,“The properties of colinear and coplanar samples,”The 1999 National Conf on Neural Networks, Shantou, China. Dec. 1999, pp.244-247.
    5. D.S.Huang,“The solution of linear equations based on neural networks,”The 1999 National Conf on Neural Networks, Shantou, China. Dec. 1999, 244-247, 248-251.
    6. D.S.Huang,“On the prospects of intelligence technology,”The first conf of Chinese Institute of science and technology, Hangzhou, Sept. 1999.
    7. Z.Liang, D.S.Huangand X.G.He,“The study of mapping mechanism of multiple-inputs and one output feedforward neural network,”The 1999 National Conf on Neural Networks, Shantou, China. Dec. 1999, pp.173-177.
    8. Z.Liang, D.S.Huangand X.G.He,“A gradient-Newton integrated BP algorithm for feedforward neural network,”The 1999 National Conf on Neural Networks, Shantou, China. Dec. 1999, pp.209-213.
    9. Z.Liang, D.S.Huangand X.G.He,“A gradient-Newton coupled learning algorithm for feedforward neural network,”The 1999 National Conf on Neural Networks, Shantou, China. Dec. 1999, pp.215-220.

     

    1998

     

    1. D.S.Huang,“The range imaging of high resolution radar using stepping frequency and its properties' analyses,”The 2th National Conf. on Signal and Information Processing, Chinese Institute of Aerospace, Jing Gangshan, China, pp.100-104, Sept.1998.
    2. D.S.Huang,“The analyses of dynamic properties for fuzzy ARTMAP classifiers,”The 2th National Conf. on Signal and Information Processing, Chinese Institute of Aerospace, Jing Gangshan, China, pp.100-104, Sept.1998.
    3. D.S.Huang,“On the selection method of hidden nodes number of feedforward neural networks and the global optimization,”The 4thNational Youth Conf of Institute of Chinese Electronics (CIE-YC’98), Beijing, China, Sept, 1998, pp.561-564.
    4. D.S.Huang,“On the study of approximation capabilities of linear neural networks,”The 6th National Conf on Bio-Physics Conf., Chendu, p.327, May 1998.

     

    1997

     

    1. D.S.Huang,“The theory of feedforward neural networks for global optimization,”Proceedings of 1997 Chinese Congress on Neurocomputing Science (CCNS'97), Nanjing,  pp.330-335, Oct.1997 (Invited Speech).
    2. D.S.Huang,“The study of classification mechanism of feedforward neural networks with nonlinear outputs,”Proceedings of 1997 Chinese Congress on Neurocomputing Science (CCNS'97), Nanjing, pp.837-840, Oct., 1997.
    3. D.S.Huang,“The merging behaviour for linear feedforward neural network classifiers,”Proceedings of 1997 Chinese Congress on Neurocomputing Science (CCNS'97), Nanjing, pp.826-830, Oct., 1997.
    4. D.S.Huang,“A method for enhanced generalization capabilities of radial basis network classifiers,”Proceedings of 1997 Chinese Congress on Neurocomputing Science (CCNS'97), Nanjing, pp.831-836, Oct., 1997.

     

    1996

     

    1. D.S.Huangand S.D.Ma,“On the development of the feedforward network classifiers,”National Conf on Neural Networks'96, Chendu, China, Oct.28-Nov.2, 1996, pp.62-66(Plenary Talk).
    2. D.S.Huang,“The one-category-multiple output node feedforward neural network classifiers,” The Symposium on Information and Control in Biologic Medicine,Aug. 1996,Huangshan, Anhui.
    3. D.S.Huang,“A theorem on generalized radial basis function network classifiers,”National Conf on Neural Networks'96, Chendu, China, Oct.28-Nov.2, 1996, pp.497-501.
    4. D.S.Huangand S.D.Ma,“The geometrical classifying mechanism of the output layer in the feedforward networks with linear output nodes,”National Conf on Neural Networks'96, Chendu, China, Oct.28-Nov.2, 1996, pp.476-479.
    5. D.S.Huang,“The study of decorrelation properties in the hidden outputs of the nonlinear feedforward networks,”National Conf on Neural Networks'96, Chendu, China, Oct.28-Nov.2, 1996, pp.480-483.
    6. D.S.Huang,“Application of linear feedforward networks to the inversion of nonsingular matrix,”National Conf on Neural Networks'96, Chendu, China, Oct.28-Nov.2, 1996, pp.493-496.
    7. D.S.Huangand S.D.Ma,“Linear feedforward network classfiers and Fisher linear discrimination,” National Conf on Neural Networks'96, Chendu, China, Oct.28-Nov.2, 1996, pp.484-488.
    8. D.S.Huang,“The one-category-multiple output node feedforward neural network classifiers,”Workshop on Information and Control in Biomedical Engineering, Aug.24-28, 1996, Huangshan, P.R.China.

     

    1995

     

    1. D.S.Huangand S.D.Ma, “The basic feature of neural networks for pattern recognition,”the National Conf in the 10th Anniversary Celebration of Chinese Postdoctor System, Beijing, Academic Press, pp.197-204,1995 (Invited Speech).
    2. D.S.Huang,“A new detection method of high resolution radar targets based on position correlation,”The National Conf in the 10th Anniversary Celebration of Chinese Postdoctor System, Beijing, Academic Press, pp.205-209, 1995.

     

    1993

     

    1. D.S.Huangand Z.Bao,“The effect of the shape parameters on the recognition performance of Gaussian radial basis function networks,”National Conf on Neural Networks'93, Xian, China, October 23-27,1993, pp.851-855.
    2. D.S.Huangand Z.Bao,“Application of generalized radial basis function networks to the recognition of radar targets,”National Conf on Neural Networks'93, Xian, China, October 23-27, 1993, pp.856-861.

     

    1991

     

    1. D.S.Huangand Z.Bao,“Signal detection under strong clutters using multilayer perceptron networks,”National Conf on Neural Networks'91, Nanjing, China, December 15-18, 1991.
    2. D.S.Huangand Z.Bao,“Adaptive cancellation of jamming and noise using improved backpropagation algorithm,”National Conf on Neural Networks'91, Nanjing, China, December 15-18, 1991.

     

    1989

     

    1. D.S.Huang, D.J.Zhu,“The study of fast adaptive frequency estimation methods for frequency-hopping signals,”The 6th Electronics Counter-measure Conference, Qingdao, China, pp.56-61,1989.

     

    1988

     

    1. D.S.Huang, D.J.Zhu,“The analyses of interference methods for frequency-hopping transmitter-receivers,”The article for Institute of Space Navigation of Hunan Province and the 35 Anniversary of the founding of National Defense University of Science and Technology, May 1988.
    2. D.S.Huang,“The study of optimal selection methods based on computers for pseudo random sequences,”The article for Institute of Space Navigation of Hunan Province and the 35 Anniversary of the founding of National Defense University of Science and Technology, May 1988.