Visual analysis and machine learning are two important techniques in most academic, industrial, business,and medical applications. Visual analysis including image and video processingsystemsis closely related to various fields, such as internet of things, automatic navigation, intelligent robots and smart healthcare, etc. Machine learning has obtained great success in vision, graphics, natural language processing, gaming, and controlling.
The workshop aims to bring together the leading researchers and developers from both academia and industry to discuss and present their latest research and innovations on the theory, algorithms, and system technologies that can substantially improve existing image processing and computer vision based on machine learning and artificial neural network. We encourage prospective authors to submit related distinguished research papers on this subject, including new theoretical methods, innovative applicationsandsystem prototypes.
Lei Chen received the B.Sc. and M.Sc. degrees in electrical engineering from Shandong University, Jinan, China, and the Ph.D. degree in electrical and computer engineering from University of Ottawa, Ontario, Canada. He is currently an Associate Professor with the School of Information Science and Engineering, Shandong University, China. His research interests include image processing and computer vision, visual quality assessmentand pattern recognition,machine learningand artificial intelligence.He was the principal investigator of projects granted from the National Natural Science Foundation of China, National Natural Science Foundation of Shandong Province, China Postdoctoral Science Foundation, etc. He has published more than 40 papers on top international journals and conferences in recent years including IEEE TIP, Signal Process., ICME, etc. He was awarded the Future Plan for Young Scholars of Shandong University. He served for the ICIGP 2021, ICIGP 2022, IoTCIT 2022, MLCCIM 2022, etc. as Technical Co-Chair or Publicity Co-Chair.