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Kernel Combined Sparse Representation for Disease Recognition
Feng Q.; Zhou Y.
2016-10-01
Source PublicationIEEE Transactions on Multimedia
ISSN15209210
Volume18Issue:10Pages:1956-1968
Abstract

Motivated by the idea that the correlation structure of the entire training set can disclose the relationship between the test sample and the training samples, we propose the combined sparse representation (CSR) classifier for disease recognition. The CSR classifier minimizes the correlation structure of the entire training set multiplied by its transposition and the sparse coefficient together for classification. Including the kernel concept, we propose the kernel combined sparse representation classifier utilizing the high-dimensional nonlinear information instead of the linear information in the CSR classifier. Furthermore, considering the information of the training samples and the class center, we then propose the center-based kernel combined sparse representation (CKCSR) classifier. CKCSR uses the center-based kernel matrix to increase the center-based information that is helpful for classification. The proposed classifiers have been evaluated by extensive experiments on several well-known databases including the EXACT09 database, Emphysema-CT database, mini-MIAS database, Wisconsin breast cancer database, and HD-PECTF database. The experimental results demonstrate that the proposed classifiers achieve better recognition rates than the sparse representation-based classification, collaborative representation based classification, and several state-of-the-art methods.

KeywordCollaborative Representation Disease Recognition Sparse Representation
DOI10.1109/TMM.2016.2602062
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000384644800004
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Cited Times [WOS]:8   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Feng Q.,Zhou Y.. Kernel Combined Sparse Representation for Disease Recognition[J]. IEEE Transactions on Multimedia,2016,18(10):1956-1968.
APA Feng Q.,&Zhou Y..(2016).Kernel Combined Sparse Representation for Disease Recognition.IEEE Transactions on Multimedia,18(10),1956-1968.
MLA Feng Q.,et al."Kernel Combined Sparse Representation for Disease Recognition".IEEE Transactions on Multimedia 18.10(2016):1956-1968.
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