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Suchendra M. Bhandarkar is a Professor of Computer Science. He received a Ph.D in Computer Engineering from Syracuse University in 1989. His research interests are in the areas of Computer Vision, Parallel Computing, and Visual Information Systems. He is also interested in the applications of Neural Networks and Genetic Algorithms to Computer Vision problems and the interdisciplinary applications of Computer Vision and Parallel Computing in areas such as Computational Biology, Genomics, Biomedicine, Intelligent Transportation Systems and Forest Resource Management. He directs the Visual and Parallel Computing Laboratory (VPCL) in the Department of Computer Science at the University of Georgia.
Dr. Bhandarkar has published extensively in the areas of Computer Vision and Parallel Computing. His research has resulted in over 100 papers of which over 50 have appeared in peer-reviewed archival journals. He has coauthored a book titled 3-D Object Recognition from Range Images (Springer-Verlag, 1992). Dr. Bhandarkar has served on the review panels of NASA, EPA, DOE and the USDA. He is an Associate Editor of The Computer Journal, The Journal of Applied Intelligence and The Journal of Machine Vision and Applications. He also serves on the technical committees for Pattern Analysis and Machine Intelligence, Parallel Processing and Multimedia Computing in the IEEE Computer Society and the technical committee for Robot Vision in the IEEE Robotics and Automation Society. Dr. Bhandarkar has also served on the program committees of various international conferences, workshops and symposia. He has also worked as a consultant to NASA, DOE and various start-up companies under the SBIR initiative. Dr. Bhandarkar is a member of the IEEE, ACM, SPIE and AAAI and the honor societies Phi Kappa Phi and Phi Beta Delta.
研究兴趣
论文共 48 篇作者统计合作学者相似作者
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2017 IEEE International Conference on Computer Vision Workshops (ICCVW) (2017): 1256-1265
arxiv(2017)
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Pattern Analysis and Applicationsno. 4 (2017): 1261-1273
2016 IEEE Winter Conference on Applications of Computer Vision (WACV)pp.1-9, (2016)
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016): 2176-2184
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