Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications (Computer Vision and Pattern Recognition)

* Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications (Computer Vision and Pattern Recognition) ✓ PDF Read by ! Zhouchen Lin, Hongyang Zhang eBook or Kindle ePUB Online free. Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications (Computer Vision and Pattern Recognition) Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. Presents a self-contained, up-to-date introduction that covers underlying theory, algorithms and the state-of-the-art in current applicationsProvides a full and clear explanation of the theory behind the modelsIncludes detailed proofs in the appendices. The main applications included are video denoising, background modeling,

Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications (Computer Vision and Pattern Recognition)

Author :
Rating : 4.94 (615 Votes)
Asin : 0128127317
Format Type : paperback
Number of Pages : 260 Pages
Publish Date : 2015-10-24
Language : English

DESCRIPTION:

Computer Vision. He is an associate editor of IEEE Trans. He is currently a Professor at Key Laboratory of Machine Perception(MOE), School of Electronics Engineering and Computer Science, Peking University. He is now a Ph.D. Pattern Analysis and Machine Intelligence and International J. He is anIAPR fellow.Hongyang Zhang received the Master’s degree in computer science from Peking University, Beijing, China in 2015. candidate in Machine LearningDep

He is now a Ph.D. He is an associate editor of IEEE Trans. About the Author Zhouchen Lin received the Ph.D. He is anIAPR fellow.Hongyang Zhang received the Master’s degree in computer science from Peking University, Beijing, China in 2015. Pattern Analysis and Machine Intelligence and International J. His research areas include computer vision, image processing, machine learning, pattern recognition, and numerical optimization. degree in applied mathematics from Peking University in 2000. He is currently a Professor at Key Laboratory of Machine Perception(MOE), School of Electronics Engineering and Computer Science, Peking University. . He is an area chair of CVPR 2014/2016, ICCV 2015 and NIPS 2015 and a senior program committee member of AAAI 2016/2017 and IJCAI 2016. candidate in Machine LearningDepartment, School of

Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. Presents a self-contained, up-to-date introduction that covers underlying theory, algorithms and the state-of-the-art in current applicationsProvides a full and clear explanation of the theory behind the modelsIncludes detailed proofs in the appendices. The main applications included are video denoising, background modeling, image align

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