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特邀香港中文大学王晓刚博士来校做学术报告

信控院特邀香港中文大学王晓刚博士来校做学术报告, 欢迎广大师生踊跃参加!

报告时间:11月15日(星期五)上午10:00-11:30

报告地点:三号学科楼S410

报告题目:Deep Learning in Object Detection, Segmentation and Recognition

主持人:刘青山院长

 

报告简介:

    Deep learning has become a major breakthrough in artificial intelligence and achieved amazing success on solving grand challenges in many fields including computer vision. In this seminar, I will introduce our recent works on developing deep models to solve several computer vision problems, including pedestrian detection, facial keypoint detection, face parsing, pedestrian parsing, face recognition, and face attribute recognition. Deep models significantly advance the state-of-the-art on these challenges because of their capability of automatically learning hierarchical feature representations from data, jointly optimizing key components in a computer vision system, and their learning capacity. Through examples, I will share our experience on how to formulate a vision problem with deep learning, how to train a deep neural network, how to make use the large learning capacity of deep models, and how to learn features in a vision application. The benefits of deep architectures will also be discussed.   

 

王晓刚博士个人简介 :

    Xiaogang Wang received his Bachelor degree in Electrical Engineering and Information Science from the Special Class of Gifted Young at the University of Science and Technology of China in 2001, M . Phil. degree in Information Engineering from the Chinese University of Hong Kong in 2004, and PhD degree in Computer Science from Massachusetts Institute of Technology in 2009. He is an assistant professor in the Department of Electronic Engineering at the Chinese University of Hong Kong since August 2009. He received the Outstanding Young Researcher in Automatic Human Behaviour Analysis A ward in 2011, Hong Kong RGC Early Career Award in 2012 , and Young Researcher Award of the Chinese University of Hong Kong . He is the associate editor of the Image and Visual Computing Journal. He was the area chair of ICCV 2011, ECCV 2014 and ACCV 2014. His research interests include computer vision, deep learning, crowd video surveillance, object detection, and face recognition.

信息与控制学院

2013/11/13

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