Classification and Boosting with Multiple Collaborative Representations
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Chi, Yuejie
Porikli, Fatih
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Institute of Electrical and Electronics Engineers (IEEE Inc)
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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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IEEE Transactions on Pattern Analysis and Machine Intelligence
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2037-12-31
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