University of California, Riverside

Department of Electrical and Computer Engineering



A Talk on “Deep Learning Networks for Computer Vision: Blessing or Curse?” ” Presented by Dr. Rama Chellappa


A Talk on “Deep Learning Networks for Computer Vision: Blessing or Curse?”....
 
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A Talk on “Deep Learning Networks for Computer Vision: Blessing or Curse?” ” Presented by Dr. Rama Chellappa

April 4, 2016 - 11:10 am
Winston Chung Hall, 205/206

Abstract

Over the last five years or so, deep learning networks have produced impressive results for several computer vision problems such as face detection, object detection/recognition and face verification. In an ongoing effort on face verification, our groups as well as several other groups have been able to improve performance using deep learning networks, which is both exhilarating and worrisome. While performance improvement using deep learning networks should be seen as a blessing (who can argue against performance?), several problems remain to be addressed. For example, reliance on the availability of very large annotated data set may be a handicap. Being able to generalize networks across test data with different distributions (domain adaptation) as well as different problems is also important. Integrating traditional models for pose, illumination and other degradations may improve performance as well as reduce the number of parameters and the amount of training data needed. Deriving bounds on the number of training samples, layers and understanding why deep networks work well will be useful for planning data acquisition/annotation tasks. We will address some of these issues in the talk.

 Biography:

Prof. Rama Chellappa is a Minta Martin Professor of Engineering and Chair of the ECE department at the University of Maryland.  Prof. Chellappa received the K.S. Fu Prize from the International Association of Pattern Recognition (IAPR). He is a recipient of the Society, Technical Achievement and Meritorious Service Awards from the IEEE Signal Processing Society and four IBM Faculty Development Awards. He also received the Technical Achievement and Meritorious Service Awards from the IEEE Computer Society. At UMD, he received college and university level recognitions for research, teaching, innovation and mentoring of undergraduate students. In 2010, he was recognized as an Outstanding ECE by Purdue University. Prof. Chellappa served as the Editor-in-Chief of PAMI. He is a Golden Core Member of the IEEE Computer Society, served as a Distinguished Lecturer of the IEEE Signal Processing Society and as the President of IEEE Biometrics Council. He is a Fellow of IEEE, IAPR, OSA, AAAS, ACM and AAAI and holds four patents.

 

 

 

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University of California, Riverside
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Electrical and Computer Engineering
Suite 343 Winston Chung Hall
University of California, Riverside
Riverside, CA 92521-0429

Tel: (951) 827-2484
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