ICIC 2022 Special Session

The ICIC 2022 Program Committee is inviting proposals for special sessions to be held during the conference(http://www.ic-icc.cn/2022/index.htm), taking place on August 7-11, 2022, in Xi'an, China.

Each special session proposal should be well motivated and should consist of 8 to 12 papers. Each paper must have the title, authors with e-mails/web sites, and as detailed an abstract as possible. The special session organizer(s) contact information should also be included. All special session organizers must obtain firm commitments from their special session presenters and authors to submit papers in a timely fashion (if the special session is accepted) and, particularly, present them at the ICIC 2022. Each special session organizer will be session chair for their own special sessions at ICIC 2022 accordingly. All planned papers for special sessions will undergo the same review process as the ones in regular sessions. All accepted papers for special sessions will also be published by Springer's Lecture Notes in Computer Sciences (LNCS)/ Lecture Notes in Artificial Intelligence (LNAI)/ Lecture Notes in Bioinformatics (LNBI).

All the authors for each special session must follow the guidelines in CALL FOR PAPERS to prepare your submitted papers.

Proposals for special sessions should be submitted in ELECTRONIC FORMAT by http://www.ic-icc.cn/icg/index.asp at Special Session.

orders
Title
Organizers
Nationality
Special Session on Visual Recognition, Processing and Automation (ViRPA)
Dakshina Ranjan Kisku
India
Special Session on recent advances in shallow and deep machine learning methods and techniques in bioinformatics
Xiaolong Zhang,Bo Li, Shihua Zhang
China
Special Session on Machine Learning Methods Applied to Computer Vision and Image Processing
Jair Cervantes, Farid Garca Lamont, Jos Sergio Ruiz Castilla, Adrian Trueba Espinosa
Mexico
Special Session on ARTIFICIAL INTELLIGENCE and Industry 4.0 FROM THEORY TO APPLICATIONS
Abir Jaafar Hussain, Dhiya Al-Jumeily, Hissam Tawfik, Jamila Mustafin, Mohamed Mahyoub
AE, UK, Russia
Special Session on Protein and Gene Bioinformatics: Analysis, Algorithms and Applications
M. Michael Gromiha, Y-h. Taguchi
India, Japan
Special Session on Intelligent Computing for Cybersecurity: Detection, Mitigation and Response in the protection of Soft Targets and Smart Cities
Marek Pawlicki, Rafal Kozik, Michal Choras
Poland

1. Special Session on Visual Recognition, Processing and Automation (ViRPA)

Organizer:
Dakshina Ranjan Kisku
National Institute of Technology Durgapur, India
Email:drkisku@cse.nitdgp.ac.in

Scope and Topics:
Humans are most intelligent species who make thousands of decisions in every single day. However, making decision needs efficient cognitive actions that create a functional mapping to the target object or thing. Generating an appropriate functional mapping with distinctive information is a difficult task on machines. To empower the machines to perform human like decisions in order to classify objects or understanding a particular scene in complex environments need proper analysis and utilization of subjective matter very well including performing specific tasks of image processing, and applicability of machine vision and pattern recognition techniques. These paradigms would help the systems to learn about the diverse environment with lots of entities in bit more typical way even with incomplete information. Therefore, to use the correct image processing and vision approaches might transform ill-treated and distorted patterns to a distinctive and unique features groups which further make the learning algorithm suitable for taking decision in real world scenario. Image processing, pattern recognition and computer vision are interlinked topics which initiated the industrial revolution in the areas of automated intelligent systems and machine perception. They solved many practical cognitive and machine vision problems with paramount competency and shaped up the digital world with illustrious examples. They have made significant contributions in the areas of image analysis, feature extraction, object recognition, image segmentation, image enhancement, biometrics, motion analysis, depth estimation, machine and deep learning, medical imaging, object detection, video processing, industrial automation, affective computing, etc. The objective of this special session is to provide a vibrant forum for students, researchers and technologists to present and share novel ideas and works in relevant areas. Contributions welcome on the topics of interest include but are not limited to Scene understanding Image and scene reconstruction Object recognition and classification Action recognition Biometrics Gesture recognition Medical, biological and microscopy imaging Image segmentation Deep learning for computer vision Object recognition Autonomous vehicles Robot vision Visual processing Big data in visual processing Video analysis, understanding and processing Semantic analysis Image compression Cognitive processing Visual healthcare systems Motion and tracking Visual reasoning Assistive systems for visually challenge individuals Text and document understanding Image and video retrieval Image and video synthesis Photograph and video editing and manipulation Natural language processing Music analysis and processing Optical character recognition.

2. Special Session on recent advances in shallow and deep machine learning methods and techniques in bioinformatics

Organizers:
Xiaolong Zhang
Wuhan University of Science and Technology, China
Email:xiaolong.zhang@wust.edu.cn

Bo Li
Wuhan University of Science and Technology, China
Email:libo@wust.edu.cn

Shihua Zhang
Wuhan University of Science and Technology, China
Email:zhangshihua@wust.edu.cn

Scope and Topics:
Statistics is a major contributor to the success of bioinformatics. High throughput technologies generate large data sets and new problems in bioinfrmatics, which urges to model many both shallow and deep machine leaning methods for controlling the false discovery rate, performing aggressive variable selection, and implementing multiway cluster analyses. Therefore authors are encouraged to submit both theoretical and applied papers about both shallow and deep machine leaning methods to solve bioinformatics related problems. Potential topics include but are not limited to the following:

  • Tumor gene expressive profiles analysis
  • LncRNA data analysis
  • miRNA data analysis
  • Single cell clustering
  • Hot pots and hot Regions predictionin PPIs
  • Drug-target interaction prediction

3. Special Session on Machine Learning Methods Applied to Computer Vision and Image Processing

Organizers:
Jair Cervantes
Autonomous University of Mexico State, Mexico
Email:jcervantesc@uaemex.mx

Farid Garca Lamont
Autonomous University of Mexico State, Mexico
Email:fgarcial@uaemex.mx

Jos Sergio Ruiz Castilla
Autonomous University of Mexico State, Mexico
Email:jsruizc@uaemex.mx

Adrian Trueba Espinosa
Autonomous University of Mexico State, Mexico
Email:atruebae@uaemex.mx

Scope and Topics:
In recent years, digital image processing and computer vision have attempted to automate the tasks that the human visual system can do. Artificial vision algorithms have been successfully applied to important fields including medicine, engineering, biology, agriculture, remote sensing, among others. To promote the development of this important area, this special session aims to explore scientific paradigms, models, methods, technologies, and applications with both solid theoretical development and practical importance, focusing on Computer Vision and Image Processing algorithms and their applications to different fields. Potential topics include, but are not limited to: Image processing Image segmentation Image restoration Object detection Object recognition Handwritten digit recognition Face detection Face recognition Texture image analysis Human activity recognition Visual scene analysis Object tracking Feature extraction Image retrieval Facial expression and emotion analysis Biological identification Action recognition Medical image analysis Remote sensing

4. Special Session on ARTIFICIAL INTELLIGENCE and Industry 4.0 FROM THEORY TO APPLICATIONS

Organizers:
Abir Jaafar Hussain
Engineering, AE
Email:abir.hussain@sharjah.ac.ae

Dhiya Al-Jumeily
Computer Science, UK
Email:d.aljumeily@ljmu.ac.uk

Hissam Tawfik
Engineering, AE
Email:htawfik@sharjah.ac.ae

Jamila Mustafin
Kazan University, Russia
Email:jamila0111@hotmail.com

Mohamed Mahyoub
Computer Science
Email:m.mahyoub@tutorreach.com

Scope and Topics:
SCOPE AND MOTIVATION Artificial Intelligence (AI), Intelligent Sensors, Robotics and more recently Industry 4.0 are research areas and applications aligned to benefit the research community and society in various domains. Sensors emit a tremendous amount of data (aka big data) which can be captured and analysed using different AI and Machine Learning (ML) tools and techniques. Extensive research has been developed in this area, ranging from theoretical foundations and principles, to practical applications in diverse context including medical, industry, environment, finance, education, to name just a few. The aim of this Special Session is allowing researchers to communicate their high-quality and original ideas by presenting and publishing innovative advances in Industry 4.0, computational intelligence and the Internet of Everything (IoE) and their applications. Topics: This special session explores the convergence of Industry 4.0, AI, data science, and their applications in Health and Medicine, providing a background to problem domains, considering the progress so far, assessing the potential of such approaches, and exploring possible future directions. We aim to increase the understanding and use of AI techniques in the medical application to real-world problems. We welcome contributions that deal with all aspects of the scientific foundations, theories, techniques and applications of computing, data and analytics, including, but not limited to:

  • Industry 4.0 applications in health and medicine
  • Biomedical Intelligence, Health Informatics and Intelligent Driven Systems
  • Advances in Medical Image and Signal Processing
  • Computational Intelligence Technology in Health and Medicine
  • Cognitive Computing and Emotional Intelligence in Health and Medicine
  • Computational Intelligence Technology in Data mining, Data Integration and Big Data Analysis for Health and Medicine
  • Concepts and Technologies of AI in Digital Health and Clinical Decision Support System
  • Predictive Models and Analytics Using Artificial Intelligence
  • Genomic and artificial intelligence solutions
  • The Application of AI in Decision Support System for different Cancer cases
  • The use of AI in Patient Care, Safety, and Monitoring

5. Special Session on Protein and Gene Bioinformatics: Analysis, Algorithms and Applications

Organizers:
M. Michael Gromiha
IIT Madras, India
Email:gromiha@iitm.ac.in

Y-h. Taguchi
Chuo University, Japan
Email:tag@granular.com

Scope and Topics:
The advanced developments in Biotechnology provide a wealth of data on genomes, proteomes, metabolomes and transcriptomes. This has been evidenced with the growth of data in gene expression profiles, amino acid sequences, protein three-dimensional structures and protein-protein interaction networks. The availability of data pave way to several analyses in biological and medical research, such as high-throughput protein structure prediction, genome-wide protein-protein interaction prediction, binding sites and interface structures in protein complexes, identification of post-transcription modification sites, single nucleotide polymorphism (SNP) prediction, gene expression profile data analysis and so on. The comprehensive analysis, development of efficient algorithms, software and tools for data integration and visualization are necessary in these cutting-edge research fields. This special session provides a forum for researchers to present and discuss their latest research results to timely identify and address related problems and challenges. We invite the submission of high-quality, original and unpublished papers in this area. Computational methods for protein and gene bioinformatics includes but are not limited to:

  • Protein structure analysis, folding and stability
  • Secondary and tertiary structure prediction of globular and membrane proteins
  • Analysis and prediction of protein-protein, protein-nucleic acid and protein-ligand interactions including contact sites, hotspots and interface
  • Modeling and Analysis on protein interaction network
  • Gene regulatory network modeling
  • Disease related single nucleotide polymorphism identification
  • Disease related cell signaling pathway identification
  • Gene expression profile data analysis

6. Special Session on Intelligent Computing for Cybersecurity: Detection, Mitigation and Response in the protection of Soft Targets and Smart Cities

Organizers:
Marek Pawlicki
Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
Email:marek.pawlicki@pbs.edu.pl

Rafal Kozik
Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
Email:rkozik@pbs.edu.pl

Michal Choras
Bydgoszcz University of Science and Technology, Bydgoszcz, Poland
Email:chorasm@pbs.edu.pl

Scope and Topics:
Cybersecurity is currently a major challenge not only in computer science and the digital world but for society in general, ranging from children to the elderly, from citizens to governments, critical infrastructures and homeland security. Cybersecurity is a crucial component in the protection of soft targets and smart cities. Intelligent computing methods are believed to be able to solve some of the problems of contemporary cybersecurity, including the detection, prevention, and mitigation of cyberattacks. The authors are encouraged to submit both theoretical and applied papers about intelligent computing methods to solve cybersecurity-related problems. Topics of interest include, but are not limited to:

  • Cyberattack detection
  • Machine learning for cybersecurity
  • Deep learning for cybersecurity
  • Malware, badware, ransomware detection
  • Stegomalware detection
  • Network security
  • Time-series methods for anomaly detection
  • Machine learning for response and mitigation in cybersecurity
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