2023 2nd International Conference on Machine Vision, Automatic Identification and Detection (MVAID 2023)

Keynote Speakers


Prof. Yulin Wang, Wuhan University, China


Experience: Yulin Wang is a full professor in the School of Computer Science, Wuhan University, China. His research interests include image and video processing, digital rights management, information security, intelligent system, e-commerce, IoT, code clone and so on. He got his PhD degree from University of London, UK. He got his master and bachelor degree from Huazhong University of Science and Technology(HUST)and Xi-Dian University respectively, both in China. Before joining the Wuhan University, he has worked in Hi-tech IT industry, including HUAWEI© and national research institute, for more than ten years. He has involved more than 15 national and international research projects. In recently 10 years, Prof. Wang has published 1 book, and 50+ journal and conference papers, including in IEEE TIP. He holds 10 authorized patents. Prof. Wang served as EiC of 2 international journals and reviewer of top IEEE and ACM journals. He also served as reviewer of Innovative talents projects and national  research funds, including National High Technology Research and Development Program of China. Prof. Wang was the external PhD advisor of Dublin City University, Ireland during 2008-2010. In recently 10 years, Prof. Wang served as chairman of more than 10 international conferences, and keynote speakers in more than 20 international conferences. Besides UK, he visited US, France,Italy, Portugal,Croatia, Australia, Germany, korea, Ireland,Singapore, Malaysia, Japan, and Hong Kong. In addition, Prof. Wang has been appointed as the deputy director of Hubei provincial science and technology commission (CAPD) since 2014.

Speech Title: Drone: from bionic flight to brain like autonomous navigation

Abstract: The control of unmanned aerial vehicle (UAV) has developed from remote control and program control to adaptive control with fault diagnosis and reconfiguration according to its own state change. In order to replace manned aircraft and perform various tasks in uncertain environment, UAV is bound to face great challenges from autonomous control. With the applications of various new technologies, the complexity of UAV system and the degree of automation of its functions are increasing. Due to the highly dynamic and uncertain combat environment and the complexity of flight tasks, planning and decision-making become a new technical challenge for UAVs. Various automatic control strategies based on program cannot meet the requirements of future advanced multi-functional UAVs for multi tasks in complex combat environment, so the improvement of autonomous flight control capability will be the main goal of UAV flight control system in the future.


Prof. Renchao Jin,Huazhong University of Science and Technology,China


Experience: He is a professor and doctoral supervisor at the Medical Image Information Research Center of the Institute of Digital Media, School of Computer Science and Technology, Huazhong University of Science and Technology. Currently, he mainly researches on deep learning, medical image processing and analysis algorithms, and medical device software development.

Main academic contributions: (1) Invented a fast algorithm for solving the famous NP-hard SAT problem based on the idea of quasi-physical and quasi-sociological, and won the gold medal in the 1996 International SAT Problem Solving Competition; (2) Invented a three-dimensional CT Liver segmentation algorithm based on the level set active contour model and a Couinaud segmentation algorithm, provided intelligent solutions for liver surgery planning. Relevant software developed in cooperation with medical equipment enterprises has been integrated into the supporting software system of their CT machine products; (3) Invented a series of computer-assisted medical diagnosis and treatment algorithms, involving radiotherapy planning, 3D CT/MRI image segmentation, registration and keypoint localization algorithms based on deep learning, etc..


Prof.  Cairong Zhao, Tongji University, China


Experience: Cairong Zhao is currently a Professor of College of Electronic and Information Engineering at Tongji University. He received a Ph.D. degree from Nanjing University of Science and Technology, an M.S. degree from Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences and a B.S. degree from Jilin University, in 2011, 2006 and 2003, respectively. He works on visual and intelligent learning, including computer vision, pattern recognition and visual surveillance. He has authored more than 40 journal and conference papers in these areas.

Speech Title: Occluded Person Re-Identification

Abstract: Person re-identification plays a vital role in intelligent video surveillance systems. However, occlusion poses significant challenges in target detection and recognition tasks. In this report, we provide a comprehensive analysis of the recent developments in occluded person re-identification. We elaborate on the four key issues caused by occlusion, namely positional displacement, scale displacement, noise information, and missing information, and discuss their solutions. Additionally, we introduce the progress and representative works of our research group in this direction. Finally, we analyze and discuss the future development trends of occluded person re-identification.