报告题目：Hyperspectral Computer Vision and Its Applications

报告人：周峻（澳大利亚格里菲斯大学教授）

报告时间：2023年10月11日（星期三）19:00

腾讯会议号：898397243

报告摘要：Hyperspectral imagery contains rich information on the spectral and spatial distribution of object materials in a scene. Traditional hyperspectral remote sensing methods mainly focus on pixel-level spectral analysis. On the contrary, computer vision has discovered color, texture, and various spatial and structural features of objects, but not spectral information.It is necessary to bridge the gap between spectral and spatial analysis in order to invent new tools for effective image analysis and understanding. This talk gives an overview of hyperspectral imaging technology and material-based spectral-spatial analysis techniques, and how they can be used to address challenges in computer vision tasks. Several case studies in object detection,image classification and video tracking will be presented in this talk, with a focus on deep learning based approaches.

报告人简介： Jun Zhou is a professor in the School of Information and Communication Technology at Griffith University, Australia. He received his BS degree in computer science from Nanjing University of Science and Technology, China, in 1996, an MS degree in computer science from Concordia University, Canada, in 2002, and the PhD degree from the University of Alberta,Canada, in 2006. Before joining Griffith University, he had been a research fellow in the Research School of Computer Science at the Australian National University and a researcher at the Canberra Research Laboratory, NICTA, Australia. His research interests include pattern recognition, computer vision and hyperspectral image processing, with their computer vision and remote sensing applications. He has published more than 200 papers in leading image processing and remote sensing venues, such as IEEE TIP, IEEE TGRS, IEEE TNNLS, PR, AAAI, IJCAI, CVPR, and ICCV. He is an associate editor of five international journals, including IEEE TGRS and Pattern Recognition