文件名称:LSL_SC
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based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the minimum representation error. While the importance of sparsity is much emphasized in SRC and many related works, the use of collaborative representation (CR) in SRC is ignored by most literature.
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下载文件列表
LSL_SC
......\demo
......\....\demo.m
......\....\demo_ar.mat
......\....\demo_yaleb.mat
......\....\dlsc_demo.m
......\....\SSCP_demo.m
......\....\USCP_demo.m
......\readme.m
......\utilities
......\.........\Classifier_NN_f.m
......\.........\content.m
......\.........\dlsc.m
......\.........\featureselection_supervised.m
......\.........\featureselection_unsupervised.m
......\.........\l1_ls_matlab
......\.........\............\l1_ls_matlab
......\.........\............\............\@partialDCT
......\.........\............\............\...........\ctranspose.m
......\.........\............\............\...........\mtimes.m
......\.........\............\............\...........\partialDCT.m
......\.........\............\............\find_lambdamax_l1_ls.m
......\.........\............\............\find_lambdamax_l1_ls_nonneg.m
......\.........\............\............\l1_ls.m
......\.........\............\............\l1_ls_nonneg.m
......\.........\............\............\l1_ls_usrguide.pdf
......\.........\............\............\operator_example.m
......\.........\............\............\README.TXT
......\.........\............\............\simple_example.m
......\.........\learnmatrixpsupervised.m
......\.........\learnmatrixpunsupervised.m
......\.........\Metaface_ICIP
......\.........\.............\Metaface_ICIP
......\.........\.............\.............\main_metaface.m
......\.........\.............\.............\ReadMe.txt
......\.........\.............\.............\utilities
......\.........\.............\.............\.........\Eigenface_f.m
......\.........\.............\.............\.........\Metaface.asv
......\.........\.............\.............\.........\Metaface.m
......\.........\.............\.............\.........\Metaface_rand.asv
......\.........\.............\.............\.........\Metaface_rand.m
......\.........\.............\.............\.........\min_1Dwhole_reconstruct_gap.asv
......\.........\.............\.............\.........\min_1Dwhole_reconstruct_gap.m
......\.........\patch_divide.m
......\.........\SSCP.m
......\.........\USCP.m