Title
Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications (Advances in Computer Vi,Used
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This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, robust and efficient sparse representation, and largescale visual recognition; covers feature representation and learning, sparsity induced similarity, and sparse representation and learningbased classifiers; discusses lowrank matrix approximation, graphical models in compressed sensing, collaborative representationbased classification, and highdimensional nonlinear learning; includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book.
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This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.