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行知论坛228:Hyperspectral Computer Vision: Background, Challenges, and Opportunities

发布人:张海霞审核人:张世刚 时间:2019-12-02浏览:553设置


报告题目:Hyperspectral Computer Vision: Background, Challenges, and Opportunities

报告人:周峻

报告时间:2019123日 下午14:30

报告地点:4001报告厅



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 develop innovative tools for effective image analysis. This talk gives an overview of hyperspectral imaging technology and how it can be used to address challenges in computer vision tasks. Several case studies, including object detection, classification, and tracking and their applications in agriculture, environment, and biomedical domains, will be covered in this talk.

报告人概况:
Jun Zhou received the B.S. degree in Computer Science and B.E. degree in International Business from Nanjing University of Science and Technology, China, in 1996 and 1998, respectively, the M.S. degree in Computer Science from Concordia University, Canada in 2002, and the Ph.D. degree in computing science from the University of Alberta, Canada, in 2006. He joined the School of Information and Communication Technology in Griffith University in 2012, where he is currently an associate professor. Prior to his appointment in Griffith University, he had been a research fellow in the Australian National University and a researcher at NICTA Canberra Lab. Dr. Zhou was a winner of the Discovery Early Career Research Award from the Australian Research Council in 2012. He is a key member of the ARC Research Hub for Driving Farming Productivity and Disease Prevention which has lodged funding for over 10 million Australian dollars over the next 5 years. His research interests are in pattern recognition, computer vision, hyperspectral imaging, and their applications to remote sensing, environmental informatics, agriculture, and biomedical domains. He is an associate editor of IEEE Transactions on Geoscience and Remote Sensing, Pattern Recognition, IET Computer Vision, and Journal of Soils and Sediments. 




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