When Computer Vision Meets RISC-V

The talk explores the intersection of Computer Vision (CV) and RISC-V, highlighting CV's role in enabling machines to interpret visual data through deep learning and pattern recognition, essential for applications such as object recognition and scene understanding. It introduces RISC-V as an open, flexible instruction set architecture widely adopted in embedded and high-performance systems. The presentation covers academic advances, including mixed-precision neural networks on RISC-V cores and decentralized machine learning frameworks for emerging RISC-V processors.

From an industrial perspective, it discusses how RISC-V-powered computer vision systems are transforming manufacturing through quality control, robotic guidance, and edge AI for smart factories, emphasizing real-time processing, memory protection, and scalability. The talk also promotes student involvement in hands-on tutorials to deepen practical skills in CV and RISC-V integration, fostering innovation in AI-enabled edge devices and Industry 4.0.

Dr. Haoliang LI is an Assistant Professor at the Department of Electrical Engineering, City University of Hong Kong. Before that, he was a Wallenberg-NTU Presidential Postdoc Fellow in the Rapid-Rich Object Search Lab of Nanyang Technological University. He obtained his Ph.D. degree from NTU in 2018, supervised by Prof. Alex C. Kot, and the BSc degree from the University of Electronic Science and Technology of China in 2013.