Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications - Softcover

Inhaltsangabe

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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