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Item Details
Title: SPARSE MODELING FOR IMAGE AND VISION PROCESSING
By: Julien Mairal, Francis Bach, Jean Ponce
Format: Paperback

List price: £82.50


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ISBN 10: 1680830082
ISBN 13: 9781680830088
Publisher: NOW PUBLISHERS INC
Pub. date: 19 December, 2014
Series: Foundations and Trends in Computer Graphics and Vision
Pages: 216
Description: In recent years, a large amount of multi-disciplinary research has been conducted on sparse models and their applications. This monograph intends to offer a self-contained view of sparse modeling for visual recognition and image processing.
Synopsis: In recent years, a large amount of multi-disciplinary research has been conducted on sparse models and their applications. In statistics and machine learning, the sparsity principle is used to perform model selection-that is, automatically selecting a simple model among a large collection of them. In signal processing, sparse coding consists of representing data with linear combinations of a few dictionary elements. Subsequently, the corresponding tools have been widely adopted by several scientific communities such as neuroscience, bioinformatics, or computer vision. The goal of this monograph is to offer a self-contained view of sparse modeling for visual recognition and image processing. More specifically, it focuses on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.
Publication: US
Imprint: now publishers Inc
Returns: Returnable
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