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Invited Sessions



  • 1. Intelligent Systems (download pdf)
    Description:
    The goal of this invited session is to bring together researchers interesting in intelligent systems. Researchers from these areas are encouraged to submit proposals to present their work related to intelligent systems. Submissions will be evaluated on the basis of their innovation, relevance, scientific contribution, and presentation.
    Submission Topics:
    • Neural Networks and Support Vector Machines
    • Image Processing
    • Intelligent Information Systems
    • Intelligent Agent
    • Inductive Learning
    • Intelligent Control
    • Sample and Feature Selection
    • Evolutionary Computation
    • Data Mining
    • Automated Reasoning
    • Knowledge-Based Systems
    • Information Retrieval and Integration
    • Machine Learning
    • Pattern Recognition
    • Robotics
    • Speech Recognition and Synthesis
    • Support Vector Machines
    • Mobile Intelligence
    • Web Intelligence
    • AI Applications
    • Computer Vision
    • Image Processing
    • Intelligent E-Learning/Tutoring
    • Semantic Web
    • RFID Applications
    • Intelligent Internet
    • Big Data
    • Computer and Communication Networks
    • Genetic Algorithms
    • Other Related Topics
    Submission Method:
    Authors must submit an electronic copy (in word or pdf) of their complete manuscript directly to the Session Organizer (smchen@mail.ntust.edu.tw) before June 15, 2022
    Organizer:
    Prof. Shyi-Ming Chen
    Department of Computer Science and Information Engineering,
    National Taiwan University of Science and Technology,
    43, Section 4, Keelung Road, Taipei, Taiwan
    smchen@mail.ntust.edu.tw
  • 2. Fuzzy Systems(download pdf)
    Description:
    The goal of this invited session is to bring together researchers interesting in fuzzy systems. Researchers from these areas are encouraged to submit proposals to present their work related to fuzzy systems. Submissions will be evaluated on the basis of their innovation, relevance, scientific contribution, and presentation.
    Submission Topics:
    • Fuzzy Reasoning
    • Fuzzy Control and Robotics
    • Fuzzy Image, Speech and Signal Processing
    • Vision and Multimedia, and Pattern Recognition
    • Fuzzy Data Mining
    • Fuzzy Database
    • Fuzzy Forecasting
    • Fuzzy Expert Systems
    • Fuzzy Neural Networks
    • Fuzzy Information Systems
    • Fuzzy Decision-Making
    • Computing with Words
    • Granular Computing
    • Rough Sets
    • Grey Systems
    • Fuzzy Data Analysis
    • Industrial, Financial, and Medical Applications
    • Applications of Fuzzy Systems
    • Soft Computing
    • Computational Intelligence
    • Other Related Topics
    Submission Method:
    Authors must submit an electronic copy (in word or pdf) of their complete manuscript directly to the Session Organizer (smchen@mail.ntust.edu.tw) before June 15, 2022
    Organizer:
    Prof. Shyi-Ming Chen
    Department of Computer Science and Information Engineering,
    National Taiwan University of Science and Technology,
    43, Section 4, Keelung Road, Taipei, Taiwan
    smchen@mail.ntust.edu.tw
  • 3. Adverarial Learning(download pdf)
    Description:
    In security-related applications, an adversary is able to fool a model by using carefully crafted samples. A traditional machine learning method may be compromised through an adversarial attack that violates the implicit assumption of the same distributions on training and test samples. This security problem may become more serious in deep learning since public dataset and pre-trained models are used more frequently in recent years, and those datasets and models can be easily compromised by a nefarious third party supplier.
    Submission Topics:
    • Adversarial Attack Method
    • Defence Method
    • Data Sanitization
    • Attack Detection
    • Vulnerability Analysis
    • Robust Learning
    • Generative Adversarial Network (GAN)
    • Adversarial Sample
    Submission Method:
    Authors must submit an electronic copy (in word or pdf) of their complete manuscript directly to the Session Organizer (patrickchan@ieee.org before June 15, 2022
    Organizer:
    Prof. Daniel Yeung
    Past President, IEEE SMC Society, USA
    danyeung@ieee.org
    Prof. Xizhao Wang
    Shenzhen University, China
    xizhaowang@ieee.org
    Dr. Patrick Chan
    South China University of Technology, China
    patrickchan@ieee.org
    Dr. Eric Tsang
    Macau University of Science and Technology, Macau
    cctsang@must.edu.mo
  • 4. Deep Processing of Unstructured Data(download pdf)
    Description:
    This session aims at exploring intelligent ways of processing in depth unstructured data in terms of feature extraction, feature selection and classification. In the context of machine learning, unstructured data normally needs to be transformed into structured data through feature extraction prior to training of classifiers. In the setting of representation learning, it is essential to learn a feature extractor that can be well generalized to unseen data, i.e. features extracted from training data need to be well applicable to test data and features that well describe test data should be present from training data. Also, feature extraction from unstructured data generally leads to high dimensionality of feature vectors. From the above points of view, it is necessary to adopt feature selection techniques to not only reduce the dimensionality but also increase the correlation between the feature space and the label space. On the other hand, in order to increase the depth of learning, it is necessary to ensure that a layer-by-layer processing of data is involved and the feature space is also updated iteratively during the learning process. Furthermore, sample representativeness is another issue that could not only result in overfitting of classifiers on training data but also increase the chance to cause insufficient generalizability of a feature extractor, i.e., if a sample set does not represent a full population of instances in a domain, it would be likely to train a classifier that overfits the sample set and to extract features that are incompatible with features that well describe unseen data. This session welcomes submissions of papers related to unstructured data processing and papers that address the above issues are particularly encouraged. All submitted papers will be evaluated on the basis of their relevance, technical merit and quality of writing.
    Submission Topics:
    • Natural Language Processing
    • Feature Extraction
    • Feature Selection
    • Feature Fusion
    • Deep learning
    • Ensemble Learning
    • Embedding Learning
    • Text Mining
    • Image Processing
    • Signal Processing
    • Computer Vision
    • Computer Graphics
    • Sentiment Analysis
    • Affective Computing
    • Emotion Detection
    • Topic Detection
    • Cyberbullying Detection
    • Cyberhate Detection
    • Social Media Analysis
    • 3D Reconstruction
    • Object Recognition
    • Activities Recognition
    • Emotion Cause Analysis
    • Other Related Topics
    Submission Method:
    Authors must submit an electronic copy (in word or pdf) of their complete manuscript directly to the Session Organizer (Liuh48@cardiff.ac.uk or li.zhang@rhul.ac.uk) before June 15, 2022
    Organizer:
    Dr. Han Liu
    School of Computer Science and Informatics,
    Cardiff University, Cardiff, UK
    Liuh48@cardiff.ac.uk
    Dr. Li Zhang
    Department of Computer Science,
    University of London, UK
    li.zhang@rhul.ac.uk
  • 5. Optimization Methods for Social Simulations(download pdf)
    Description:
    In this session, we discuss about optimization methods for social simulations. In social simulations, there are many optimization problems to be solved. They have many parameters to be optimized to fit existing cases. After developing simulation models, combinations of parameters in a policy should be optimized to find a better policy.
    Submission Topics:
    • local search algorithms
    • simulated annealing
    • taboo search
    • evolutionary computation
    Submission Method:
    Authors must submit an electronic copy (in word or pdf) of their complete manuscript directly to the Session Organizer (y-goto@shibaura-it.ac.jp or murata@kansai-u.ac.jp) before June 15, 2022
    Organizer:
    Prof. Yusuke Goto
    Shibaura Institute of Technology, Japan
    y-goto@shibaura-it.ac.jp
    Prof. Tadahiko Murata
    Kansai University, Japan
    murata@kansai-u.ac.jp
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