Assoc. Prof. Sinh Van Nguyen School of Computer Science and Engineering
International University
Vietnam National University
Ho Chi Minh City
Vietnam
e-mail:
nvsinh@hcmiu.edu.vnAssoc. Prof. Luu Phuong Vo School of Computer Science and Engineering
International University
Vietnam National University
Ho Chi Minh City
Vietnam
e-mail:
vtlphuong@hcmiu.edu.vnAssoc. Prof. Loan T.T. Nguyen School of Computer Science and Engineering
International University
Vietnam National University
Ho Chi Minh City
Vietnam
e-mail:
nttloan@hcmiu.edu.vn
The DMRLIP 2025 Special Session at the 16th International Conference on Computational Collective Intelligence (ICCCI 2025) brings together researchers, practitioners, and industry professionals to explore the synergy between Data Mining, Reinforcement Learning, and Image Processing. These three domains are pivotal in solving complex real-world problems in healthcare, security, autonomous systems, and industrial automation and games. This special session will focus on innovative techniques, interdisciplinary approaches, and cutting-edge applications that leverage the power of data mining to uncover insights, reinforcement learning for decision-making, and image processing for visual data interpretation. Attendees can share ideas, collaborate, and contribute to advancing the state-of-the-art in these domains.
The scope of the DMRLIP 2025 includes, but is not limited to the following topics:
The scope of the session includes, but is not limited to, the following topics:
- Advanced data mining techniques for extracting meaningful insights from large datasets.
- Applications of Reinforcement Learning in dynamic environments, such as robotics and autonomous vehicles.
- Integration of image processing and reinforcement learning for visual decision-making systems.
- Hybrid frameworks combining data mining, reinforcement learning, and image processing for interdisciplinary applications.
- Novel algorithms for multi-agent reinforcement learning in real-world scenarios.
- Image segmentation, classification, and recognition using AI-powered techniques.
- Data mining for healthcare applications, including disease prediction and medical image analysis.
- Explainable AI approaches for reinforcement learning and image processing models.
- Optimizing reinforcement learning models with insights from data mining techniques.
- AI-driven solutions for industrial automation using image processing and decision-making systems
