Visual categorization robust to large intra-class variations using entropy-guided codebook

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dc.contributor.authorKim, S.ko
dc.contributor.authorKweon, In-Soko
dc.contributor.authorLee, C.-W.ko
dc.date.accessioned2010-12-01T09:06:59Z-
dc.date.available2010-12-01T09:06:59Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2007-04-10-
dc.identifier.citation2007 IEEE International Conference on Robotics and Automation, ICRA'07, pp.3793 - 3798-
dc.identifier.issn1050-4729-
dc.identifier.urihttp://hdl.handle.net/10203/20609-
dc.description.sponsorshipThis work was supported in part by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government(MOST)(No. M1-0302-00-0064), by the MIC for the project, “Development of Cooperative Networkbased Humanoids’ Technology” of Korea.en
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherIEEE-
dc.titleVisual categorization robust to large intra-class variations using entropy-guided codebook-
dc.typeConference-
dc.identifier.wosid000250915303132-
dc.identifier.scopusid2-s2.0-36348993205-
dc.type.rimsCONF-
dc.citation.beginningpage3793-
dc.citation.endingpage3798-
dc.citation.publicationname2007 IEEE International Conference on Robotics and Automation, ICRA'07-
dc.identifier.conferencecountryIT-
dc.identifier.conferencelocationRome-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorKweon, In-So-
dc.contributor.nonIdAuthorKim, S.-
dc.contributor.nonIdAuthorLee, C.-W.-
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