Cheng Sparse Representation, Modeling and Learning in Visual Recognition
1. Auflage 2015
ISBN: 978-1-4471-6714-3
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
Theory, Algorithms and Applications
E-Book, Englisch, 257 Seiten
Reihe: Computer Science (R0)
ISBN: 978-1-4471-6714-3
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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.




