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Invited Speakers

 

Prof. Bin Chen
Harbin Institute of Technology, Shenzhen, China

 

 

 

Biography: Bin Chen is a doctoral researcher at the International Research Institute for Artificial Intelligence, Harbin Institute of Technology, Shenzhen, since 2020 and He is also a doctoral supervisor at the University of Chinese Academy of Sciences since 2006. He received his B.D.,M.D., and Ph.D. from Tsinghua University, Sichuan University and Chinese Academy of Sciences, respectively. His research interests involve machine vision, deep learning, MLLM. He has published multiple papers in top conferences such as CVPR, AAAI, NeurIPS, and ACM MM, and has been granted over 20 invention patents. The high-speed machine vision industrial defect detection system he led in development has been promoted and applied across multiple industries, generating cumulative sales exceeding 2 billion CNY.

 

 

 

 

Prof. Zhenghao Shi
Xi'an University of Technology, China

 

 

 

Biography: Zhenghao Shi, Ph.D., Professor and Doctoral Supervisor, Member of the Academic Committee of Xi'an University of Technology, Distinguished Member of CCF, "500 Elite Talents" of Taizhou City, Zhejiang Province, Chair of the Computer Vision Technology Professional Committee of the Shaanxi Computer Federation, Deputy Chair of the Biomedical Intelligent Computing Professional Committee of the Shaanxi Computer Federation, and Leader of the Research Team on Intelligent Image Processing and Application at Xi'an University of Technology. His main research interests include machine vision, medical image processing, and machine learning. He has published or accepted 40 academic papers as the first author or corresponding author. He has been awarded the Second Prize of Shaanxi Provincial Science and Technology Progress Award (ranking first), the Second Prize of Xi'an Science and Technology Progress Award (ranking first), and the Second Prize of Shaanxi Higher Education Science and Technology Award (ranking first) twice.

Speech Title: Image Enhancement for Challenging Low-Light Environments

Abstract: In practical applications, the enhancement processing of low light and low illumination images has always faced the problem of low efficiency and low quality. This report will introduce the research progress of this issue based on our practical experience in this field in the past two years, with a focus on reporting our work and achievements in using deep learning methods for low light image enhancement.

 

 

 

 

Assoc. Prof. Feifei Gu
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

 

 

 

Biography: Dr. Feifei Gu received her PhD in Instrument Science and Technology from Xi’an Jiaotong University. She is currently an Associate Researcher at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and a distinguished talent funded by Shenzhen Pengcheng Peacock Program. She supervises postgraduate students at Shenzhen University of Technology, the University of Chinese Academy of Sciences and Xi’an Technological University. Her main research focuses on computer 3D vision, image processing and optical measurement.
As the principal investigator, Dr. Gu has undertaken 10 national and provincial research projects. She also participates in 14 major research tasks including the National Natural Science Foundation of China and Guangdong Key R&D Program. She has published more than 60 papers in authoritative international journals such as Optics Express and Optics and Laser Technology, and holds nearly 20 authorized invention patents. Her research contributions have earned her the Second Prize of Shaanxi Provincial Science and Technology Progress, as well as the honor of Outstanding Innovative Young Talent of Shenzhen.