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Classification and Boosting with Multiple Collaborative Representations

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Date

2014

Authors

Chi, Yuejie
Porikli, Fatih

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

Recent advances have shown a great potential to explore collaborative representations of test samples in a dictionary composed of training samples from all classes in multi-class recognition including sparse representations. In this paper, we present two

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Keywords

Citation

URI

http://hdl.handle.net/1885/36124

Collections

ANU Research Publications

Source

IEEE Transactions on Pattern Analysis and Machine Intelligence

Type

Journal article

Book Title

Entity type

Access Statement

License Rights

DOI

10.1109/TPAMI.2013.236

Restricted until

2037-12-31

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01_Chi_Classification_and_Boosting_2014.pdf (1.84 MB)

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