Special Session 2 - Deep Learning for Intelligent Systems and Pattern Recognition

  • Submission Link: https://www.easychair.org/conferences/?conf=prai2024
    (Select Track Special Session 2: Deep Learning for Intelligent Systems and Pattern Recognition)

    Important Date:
    Submission deadline: 2024.06.15
    Notification deadline: 2024.07.05

    Deep learning has revolutionized various fields, including artificial intelligence, computer vision, natural language processing, and more. This special session aims to explore the latest developments in deep learning techniques, applications, and methods in the context of intelligent systems and pattern recognition. We will bring together researchers, practitioners, and experts to discuss and share their insights, research findings, and innovations in the field.

    Topics of interest include, but are not limited to:
    - Deep learning models and architectures for pattern recognition.
    - Intelligent systems powered by deep learning.
    - Applications of deep learning in computer vision and image recognition.
    - Natural language processing and understanding using deep learning.
    - Transfer learning and domain adaptation in intelligent systems.
    - Explainable AI and interpretable deep learning models.
    - Deep reinforcement learning for intelligent systems.
    - Human-computer interaction and deep learning.
    - Ethical and responsible AI in intelligent systems.


    Organizers:

    Uzair Aslam Bhatti, Hainan University, School of information and communication engineering, Hainan University  (uzair@hainanu.edu.cn)
    Tang Hao, Hainan University, School of information and communication engineering, Hainan University  (melineth@hainanu.edu.cn)
    Muhammad Aamir, College of Computer Science, Huanggang Normal University, Huanggang 438000, China

    For any inquiries or additional information, please contact the session organizers at uzair@hainanu.edu.cn

    Session on "Deep Learning for Intelligent Systems and Pattern Recognition" will provide a valuable opportunity for the research community to collaborate and advance the state of the art in this dynamic and evolving field.