FUSION
Studies the basic theory of multi-source, cross-domain, multi-modal, multi-view and multi-scale information fusion for big data, and explores a general artificial intelligence algorithm with strong interpretability.
Across the research fields of computer vision, natural language processing, and data mining, focusing on the efficient expression of multi-source, multi-modal, multi-view data and collaborative learning mechanisms.
For the actual needs and real data of enterprises, apply intelligent information fusion algorithms to create practical value.
Intelligent Information Fusion Research Group is affiliated with the Multimedia Technology and Graphic Image Processing Team of the School of Computer Science, South China University of Technology. The research group's research goal is multi-source, cross-domain, multi-modal, multi-view, multi-scale information fusion theory and application for big data. At present, the outputs of our group have been deeply studied and verified in many fields such as computer vision, spatio-temporal data analysis, and web data analysis.
Mentor: Lv Jianming (School of Computer Science and Engineering, South China University of Technology)
