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Hashing big multimedia data for real-time search

Title:Hashing big multimedia data for real-time search

Speaker: Heng-Tao Shen

Time: 2018.09.03 10:30AM

Venue:East main-buliding 10-103

Abstract: As the amount of multimedia data keeps growing rapidly, real-time access and retrieval from large-scale multimedia data has been the bottleneck for many real-world applications. Many research results have shown the promising performance of hashing techniques that map high-dimensional feature vectors into short binary codes for quick matching. In this talk, we will discuss the recent development on hashing to effectively support tasks such as retrieval and classification. 

Bio:Heng-Tao Shen is a Professor of National "Thousand Talents Plan", Dean of School of Computer Science and Engineering, and Director of Center for Future Media at the University of Electronic Science and Technology of China (UESTC). He is also an Honorary Professor at the University of Queensland. He obtained his BSc with 1st class Honours and PhD from Department of Computer Science, National University of Singapore in 2000 and 2004 respectively. His research interests mainly include Multimedia Search, Computer Vision, Artificial Intelligence, and Big Data Management. Heng-Tao has made continuous contributions to big multimedia data indexing and retrieval, and developed the first real-time near-duplicate video retrieval system. He has published 200+ peer-reviewed papers, among which most appeared in top-ranked publication venues,and received 7 Best Paper Awards. He received the Chris Wallace Award in 2010 conferred by Computing Research and Education Association, Australasia, and the Future Fellowship from Australia Research Council in 2012.