Low-Rank and Sparse Modeling for Visual Analysis

Low-Rank and Sparse Modeling for Visual Analysis

Paperback (01 Oct 2016)

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Publisher's Synopsis

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.

Book information

ISBN: 9783319355672
Publisher: Springer International Publishing
Imprint: Springer
Pub date:
DEWEY: 006.37
DEWEY edition: 23
Language: English
Number of pages: 236
Weight: 3752g
Height: 235mm
Width: 155mm
Spine width: 13mm