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Sparse representation based classification has attracted much attention due to its robustness in the fields of biometrics, such as face recognition, palm-print recognition. SRC first constructs the linear representation model for the test sample, and then it classifies the test sample by comparing its coding error of each class. The coding error essentially can be viewed as the distance from sample...
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