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Item Details
Title: LOW-RANK AND SPARSE MODELING FOR VISUAL ANALYSIS
By: Yun Fu (Editor)
Format: Paperback

List price: £76.50


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 3319355678
ISBN 13: 9783319355672
Publisher: SPRINGER INTERNATIONAL PUBLISHING AG
Pub. date: 23 September, 2016
Edition: Softcover reprint of the original 1st ed. 2014
Pages: 236
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.
Illustrations: 32 Tables, black and white; 51 Illustrations, color; 15 Illustrations,
Publication: Switzerland
Imprint: Springer International Publishing AG
Returns: Non-returnable
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HUMAN ACTIVITY RECOGNITION AND PREDICTIO (PB)
HUMAN ACTIVITY RECOGNITION AND PREDICTION (HB)
HUMAN-CENTERED SOCIAL MEDIA ANALYTICS (HB)
HUMAN-CENTERED SOCIAL MEDIA ANALYTICS (PB)
KOREAN MODERN: THE MATTER OF IDENTITY (HB)
LEARNING REPRESENTATION FOR MULTI-VIEW DATA ANALYSIS (HB)
LOW-RANK AND SPARSE MODELING FOR VISUAL ANALYSIS (HB)
MANIFOLD LEARNING THEORY AND APPLICATIONS
MANIFOLD LEARNING THEORY AND APPLICATIONS
MANIFOLD LEARNING THEORY AND APPLICATIONS
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ROBUST REPRESENTATION FOR DATA ANALYTICS
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THIS IS NOT AVAILABLE 011119

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