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dc.contributor.authorSaraç, Mustafa İlkeren_US
dc.contributor.authorişcen, Ahmeten_US
dc.contributor.authorGölge, Erenen_US
dc.contributor.authorDuygulu, Pınaren_US
dc.coverage.spatialVienna, Austria
dc.date.accessioned2016-02-08T12:11:41Z
dc.date.available2016-02-08T12:11:41Z
dc.date.issued2015-03-04en_US
dc.identifier.urihttp://hdl.handle.net/11693/28119
dc.descriptionDate of Conference: 29 March - 2 April, 2015
dc.descriptionConference name: Advances in Information Retrieval 37th European Conference on IR Research, ECIR 2015
dc.description.abstractWe introduce ConceptFusion, a method that aims high accuracy in categorizing large number of scenes, while keeping the model relatively simpler and efficient for scalability. The proposed method combines the advantages of both low-level representations and high-level semantic categories, and eliminates the distinctions between different levels through the definition of concepts. The proposed framework encodes the perspectives brought through different concepts by considering them in concept groups that are ensembled for the final decision. Experiments carried out on benchmark datasets show the effectiveness of incorporating concepts in different levels with different perspectives. © Springer International Publishing Switzerland 2015.en_US
dc.language.isoEnglishen_US
dc.source.titleAdvances in Information Retrieval 37th European Conference on IR Research, ECIR 2015en_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-319-16354-3_7
dc.subjectConceptsen_US
dc.subjectScene recognitionen_US
dc.subjectSemanticsen_US
dc.subjectBenchmark datasetsen_US
dc.subjectEnsemble of classifiersen_US
dc.subjectFinal decisionen_US
dc.subjectHigh level semanticsen_US
dc.subjectLow level representationen_US
dc.subjectScene classificationen_US
dc.subjectInformation retrievalen_US
dc.titleConceptfusion: A flexible scene classification frameworken_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage55en_US
dc.citation.epage60en_US
dc.identifier.doi10.1007/978-3-319-16354-3_7
dc.publisherSpringeren_US


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