Bilkent University at TRECVID 2007

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dc.contributor.authorAksoy, Selimen_US
dc.contributor.authorDuygulu, Pınaren_US
dc.contributor.authorAksoy, C.en_US
dc.contributor.authorAydin, E.en_US
dc.contributor.authorGunaydin, D.en_US
dc.contributor.authorHadimli, K.en_US
dc.contributor.authorKoç L.en_US
dc.contributor.authorOlgun, Y.en_US
dc.contributor.authorOrhan, C.en_US
dc.contributor.authorYakin G.en_US
dc.coverage.spatialGaithersburg, MD, USAen_US
dc.date.accessioned2016-02-08T11:45:23Z
dc.date.available2016-02-08T11:45:23Z
dc.date.issued2007en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: November 2007en_US
dc.description.abstractWe describe our fourth participation, that includes two high-level feature extraction runs, and one manual search run, to the TRECVID video retrieval evaluation. All of these runs have used a system trained on the common development collection. Only visual information, consisting of color, texture and edge-based low-level features, was used.en_US
dc.identifier.urihttp://hdl.handle.net/11693/27128en_US
dc.language.isoEnglishen_US
dc.publisherNational Institute of Standards and Technologyen_US
dc.source.titleTRECVID 2007 workshop participants notebook papersen_US
dc.subjectFeature extractionen_US
dc.subjectEdge-baseden_US
dc.subjectHigh-level feature extractionsen_US
dc.subjectLow-level featuresen_US
dc.subjectTRECVIDen_US
dc.subjectVideo retrievalen_US
dc.subjectVisual informationen_US
dc.subjectImage retrievalen_US
dc.titleBilkent University at TRECVID 2007en_US
dc.typeConference Paperen_US

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