Sparse representation and learning in visual recognition: Theory and applications
Abstract
Sparse representation and learning has been widely used in computational intelligence, machine learning, computer vision and pattern recognition, etc. Mathematically, solving sparse representation and learning involves seeking the sparsest linear combination of basis functions from an overcomplete dictionary. A rational behind this is the sparse connectivity between nodes in human brain. This paper presents a survey of some recent work on sparse...
Paper Details
Title
Sparse representation and learning in visual recognition: Theory and applications
Published Date
Jun 1, 2013
Journal
Volume
93
Issue
6
Pages
1408 - 1425
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