Special Session Ⅰ- Advanced Coding and Modulations
Chair: Pingping Chen, Fuzhou University, China
Special Session Ⅱ - 6G Communications
Chair: Tianming Ma, Shanghai University Of Engineering Science, China
Special Session Ⅲ - Quantum Signal Processing
Chairs: Yajuan Xue, Chengdu University of Information Technology, China
Xing-jian Wang, Chengdu University of Technology, China
Special Session Ⅳ - Communication Security and Encryption Technology
Chair: Erfu Wang, Heilongjiang University, China
Special Session Ⅴ - Trustworthy AI
Chair: Li Li, Beijing Information Science and Technology University, China
Special Session Information
With the rapid development of artificial intelligence technology, its reliability and credibility have also received increasing attention. Developing trustworthy AI requires attention to technical issues such as its interpretability, robustness, and privacy protection.
Below is an incomplete list of potential topics to be covered in the Special Session:
Theory construction and analysis of interpretability of the deep learning/ the robustness of the machine learning and the data security.
Privacy Protection Theory and Technology.
Software vulnerability mining and information security.
Trustworthy models and theories for data mining and machine learning.
Special Session Ⅵ - Large Models
Chair: GuoJun Mao, Fujian University of Technology
Co-Chair: Shuli Xing, Fujian University of Technology
Special Session Information:
The rapid development of large models has attracted widespread attention from all walks of life. However, there are still many challenges in the design and deployment of these models. Efficiently addressing these challenges is crucial for further advancing the development of large models.
Below is an incomplete list of potential topics to be covered in the Special Session:
Theoretical construction for large model interpretability.
Ways to enhance logical reasoning in larger models.
Methods for improving the stability and generalizability of large models.
Ensuring the security and legitimacy of large models.
Special Session Ⅶ - Deep learning and its application
Chair: GuoJun Mao, Fujian University of Technology
Co-chair: Shuli Xing, Fujian University of Technology
Special Session Information:
Deep neural networks have gradually become mainstream data analysis models in many research areas due to their outstanding performance. Common deep neural network models include Convolutional Neural Networks, Graph Neural Networks, Transformer models, and their variants. This Special Issue focuses on collecting excellent application cases of deep learning models.
Below is an incomplete list of potential topics to be covered in the Special Session:
The feasibility and sustainability of research.
The high efficiency and cost-effectiveness demonstrated by deep learning models in a practical scenario.
The advancement and rationality of deep learning models in a specific application.