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Sparse Representation-based Classification

Sparse Representation-based Classification is the task based on the description of the data as a linear combination of few building blocks - atoms - taken from a pre-defined dictionary of such fundamental elements.

Papers

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Showing 21–30 of 49 papers

TitleStatusHype
Latent Dictionary Learning for Sparse Representation based Classification—0
Learning a Representation with the Block-Diagonal Structure for Pattern Classification—0
Masked Face Image Classification with Sparse Representation based on Majority Voting Mechanism—0
Minimalistic Unsupervised Learning with the Sparse Manifold Transform—0
Neighborhood Preserved Sparse Representation for Robust Classification on Symmetric Positive Definite Matrices—0
Non-intrusive Load Monitoring via Multi-label Sparse Representation based Classification—0
Optimized Projection for Sparse Representation Based Classification—0
Regularized Robust Coding for Face Recognition—0
Robust Face Recognition via Adaptive Sparse Representation—0
Semi-Supervised Sparse Representation Based Classification for Face Recognition with Insufficient Labeled Samples—0
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