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Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications - Softcover
Synopsis
Part I: Introduction and Fundamentals
Introduction
The Fundamentals of Compressed Sensing
Part II: Sparse Representation, Modeling and Learning
Sparse Recovery Approaches
Robust Sparse Representation, Modeling and Learning
Efficient Sparse Representation and Modeling
Part III: Visual Recognition Applications
Feature Representation and Learning
Sparsity Induced Similarity
Sparse Representation and Learning Based Classifiers
Part IV: Advanced Topics
Beyond Sparsity
Appendix A: Mathematics
Appendix B: Computer Programming Resources for Sparse Recovery Approaches
Appendix C: The source Code of Sparsity Induced Similarity
Appendix D: Derivations
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