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dc.contributor.authorZhao, Fen_US
dc.contributor.authorHuang, Yen_US
dc.contributor.authorWang, Len_US
dc.contributor.authorXiang, Ten_US
dc.contributor.authorTan, Ten_US
dc.date.accessioned2016-06-03T13:08:49Z
dc.date.available2016-02-19en_US
dc.date.issued2016-09en_US
dc.date.submitted2016-05-23T10:38:17.164Z
dc.identifier.issn0920-5691en_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/12663
dc.description.sponsorshipThis work is jointly supported by National Basic Research Program of China (2012CB316300), National Natural Science Foundation of China (61525306, 61573354, 61135002, 61420106015), and Strategic Priority Research Program of the CAS (XDB02070100).en_US
dc.format.extent329 - 345en_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF COMPUTER VISIONen_US
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/s11263-016-0896-3
dc.subjectRepresentation learningen_US
dc.subjectVideo analysisen_US
dc.subjectRestricted Boltzmann Machineen_US
dc.subjectSparse Bayesian learningen_US
dc.titleLearning Relevance Restricted Boltzmann Machine for Unstructured Group Activity and Event Understandingen_US
dc.typeArticle
dc.rights.holder© Springer Science+Business Media New York 2016
dc.identifier.doi10.1007/s11263-016-0896-3en_US
pubs.author-urlhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000380270000008&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6aen_US
pubs.issue3en_US
pubs.notesNot knownen_US
pubs.organisational-group/Queen Mary University of London
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Electronic Engineering and Computer Science - Staff
pubs.publication-statusPublisheden_US
pubs.volume119en_US


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