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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 31–40 of 49 papers

TitleStatusHype
Shapelet-based Sparse Representation for Landcover Classification of Hyperspectral Images—0
Single-Sample Face Recognition with Image Corruption and Misalignment via Sparse Illumination Transfer—0
Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment—0
Sparse Recovery via Bootstrapping: Collaborative or Independent?—0
Sparse Representation-Based Classification: Orthogonal Least Squares or Orthogonal Matching Pursuit?—0
Sparse Representation Classification With Manifold Constraints Transfer—0
Stable and Compact Face Recognition via Unlabeled Data Driven Sparse Representation-Based Classification—0
Structured Occlusion Coding for Robust Face Recognition—0
Study on Sparse Representation based Classification for Biometric Verification—0
Subspace-Sparse Representation—0
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