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dc.contributor.authorde Souza Gazolli, Kelly Assis
dc.contributor.authorSalles, Evandro Ottoni Teattini
dc.contributor.editorSkala, Václav
dc.date.accessioned2014-01-07T11:36:13Z
dc.date.available2014-01-07T11:36:13Z
dc.date.issued2013
dc.identifier.citationJournal of WSCG. 2013, vol. 21, no. 1, p. 41-48.en
dc.identifier.issn1213–6972 (hardcopy)
dc.identifier.issn1213-6980 (CD-ROM)
dc.identifier.issn1213–6964 (on-line)
dc.identifier.urihttp://wscg.zcu.cz/WSCG2013/!_2013_J_WSCG-1.pdf
dc.identifier.urihttp://hdl.handle.net/11025/6868
dc.description.abstractScene classification is a useful, yet challenging problem in computer vision. Two important tasks for scene classification are the image representation and the choice of the classifier used for decision making. This paper proposes a new technique for scene classification using combined classifiers method. We run two classifiers based on different features: GistCMCT and spatial MCT and combine the output results to obtain the final class. In this way, we improve accuracy, by taking advantage from the qualities of the two descriptors, without increasing the final size of the feature vector. Experimental results on four used datasets demonstrate that the proposed methods could achieve competitive performance against previous methods.en
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - Union Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectklasifikace scénycs
dc.subjectpočítačové viděnícs
dc.subjectvizuální deskriptorycs
dc.titleUsing holistic features for scene classification by combining classifiersen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedscene classificationen
dc.subject.translatedcomputer visionen
dc.subject.translatedvisual descriptorsen
dc.type.statusPeer-revieweden
Appears in Collections:Volume 21, Number 1 (2013)

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