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Structural Atomic Representation for Classification
Yuan Yan Tang1; Yulong Wang1; Luoqing Li2; C. L. Philip Chen1
2015-12-01
Source PublicationIEEE Transactions on Cybernetics
ISSN2168-2267
Volume45Issue:12Pages:2905-2913
Abstract

Recently, a large family of representation-based classification methods have been proposed and attracted great interest in pattern recognition and computer vision. This paper presents a general framework, termed as atomic representation-based classifier (ARC), to systematically unify many of them. By defining different atomic sets, most popular representation-based classifiers (RCs) follow ARC as special cases. Despite good performance, most RCs treat test samples separately and fail to consider the correlation between the test samples. In this paper, we develop a structural ARC (SARC) based on Bayesian analysis and generalizing a Markov random field-based multilevel logistic prior. The proposed SARC can utilize the structural information among the test data to further improve the performance of every RC belonging to the ARC framework. The experimental results on both synthetic and real-database demonstrate the effectiveness of the proposed framework.

KeywordAtomic Representation (Ar) Bayesian Analysis Greedy Coordinate Descent Markov Random Field (Mrf) Subspace
DOIhttps://doi.org/10.1109/TCYB.2015.2389232
URLView the original
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000365320300023
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
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Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorLuoqing Li
Affiliation1.Faculty of Science and Technology, University of Macau, Macau 999078, China.
2.Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, China
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Yuan Yan Tang,Yulong Wang,Luoqing Li,et al. Structural Atomic Representation for Classification[J]. IEEE Transactions on Cybernetics,2015,45(12):2905-2913.
APA Yuan Yan Tang,Yulong Wang,Luoqing Li,&C. L. Philip Chen.(2015).Structural Atomic Representation for Classification.IEEE Transactions on Cybernetics,45(12),2905-2913.
MLA Yuan Yan Tang,et al."Structural Atomic Representation for Classification".IEEE Transactions on Cybernetics 45.12(2015):2905-2913.
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