Rama Chellappa

Rama ChellappaProf. Rama Chellappa received the B.E. (Hons.) degree from the University of Madras, India, in 1975 and the M.E. (Distinction) degree from Indian Institute of Science, Bangalore, in 1977. He received M.S.E.E. and Ph.D. Degrees in Electrical Engineerig from Purdue University, West Lafayette, IN, in 1978 and 1981 respectively. Since 1991, he has been a Professor of Electrical Engineering and an affiliate Professor of Computer Science at University of Maryland, College Park. He is also affiliated with the Center for Automation Research (Director) and the Institute for Advanced Computer Studies (Permanent Member). In 2005, he was named a Minta Martin Professor of Engineering. Prior to joining the University of Maryland, he was an Assistant (1981-1986) and Associate Professor (1986-1991) and Director of the Signal and Image Processing Institute (1988-1990) at University of Southern California, Los Angeles.
Over the last 29 years, he has published numerous book chapters, peer-reviewed journal and conference papers. He has co-authored and edited books on MRFs, face and gait recognition and collected works on image processing and analysis. His current research interests are face and gait analysis, markerless motion capture, 3D modeling from video, image and video-based recognition and exploitation and hyper spectral processing.
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1.
Unconstrained Face Recognition
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01 Nov 2005
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Pattern Recognition37 %
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02 Jan 2025
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Pattern Recognition37 %
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Pattern Recognition37 %
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Pattern Recognition37 %
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Pattern Recognition37 %
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Pattern Recognition37 %
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Pattern Recognition37 %
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Pattern Recognition37 %
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03 Jan 2025
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Computer Vision - Accv 202237 %
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23 Feb 2023
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Computer Vision - Accv 202237 %
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11 Mar 2023
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Computer Vision - Accv 202237 %
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Computer Vision - Accv 202237 %
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Computer Vision - Accv 202237 %
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Computer Vision - Accv 202237 %
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Computer Vision - Accv 202237 %
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09 Mar 2023
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Can We Trust Ai?38 %
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06 Dec 2022
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Deep Learning-Based Face Analytics37 %
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18 Aug 2022
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Deep Learning-Based Face Analytics37 %
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21 Sep 2021
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20.
Sparse Representations and Compressive Sensing for Imaging and Vision37 %
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08 Feb 2013
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