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Learning sufficient representation for spatio-temporal deep network using information filter

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dc.citedby1
dc.contributor.authorHu Y.en_US
dc.contributor.authorNeoh D.T.H.en_US
dc.contributor.authorSahari K.S.M.en_US
dc.contributor.authorLoo C.K.en_US
dc.contributor.authorid56096604000en_US
dc.contributor.authorid56942483000en_US
dc.contributor.authorid57218170038en_US
dc.contributor.authorid55663408900en_US
dc.date.accessioned2023-05-16T02:46:23Z
dc.date.available2023-05-16T02:46:23Z
dc.date.issued2014
dc.description.abstractThis article introduced an improved spatio - temporal deep network based on information filter method for learning sufficient representation. The proposed method aims to improve feature learning capability while modeling spatial and temporal dependencies. Experiments on pattern recognition are conducted to validate the effectiveness of the proposed method. © 2014 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7028116
dc.identifier.doi10.1109/SII.2014.7028116
dc.identifier.epage658
dc.identifier.scopus2-s2.0-84946193982
dc.identifier.spage655
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84946193982&doi=10.1109%2fSII.2014.7028116&partnerID=40&md5=b2fdd414903d11217d4ef6780ca3cf2b
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/21973
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2014 IEEE/SICE International Symposium on System Integration, SII 2014
dc.titleLearning sufficient representation for spatio-temporal deep network using information filteren_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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