dc.contributorSucar, Luis Enrique
dc.contributorMontes-y-Gómez, Manuel
dc.creatorEscalante, Hugo Jair
dc.date.accessioned2013-04-04T18:16:18Z
dc.date.available2013-04-04T18:16:18Z
dc.date.created2013-04-04T18:16:18Z
dc.date.issued2012-03-05
dc.identifierRevista Computación y Sistemas; Vol. 16 No. 1
dc.identifier1405-5546
dc.identifierhttp://www.repositoriodigital.ipn.mx/handle/123456789/14825
dc.description.abstractAbstract. We present methods for image annotation and retrieval based on semantic cohesion among terms. On the one hand, we propose a region labeling technique that assigns an image the label that maximizes an estimate of semantic cohesion among candidate labels associated to regions in segmented images. On the other hand, we propose document representation techniques based on semantic cohesion among multimodal terms that compose images. We report experimental results that show the effectiveness of the proposed techniques. Additionally, we describe an extension of a benchmark collection for evaluation of the proposed techniques.
dc.languageen_US
dc.publisherRevista Computación y Sistemas; Vol. 16 No. 1
dc.relationRevista Computación y Sistemas;Vol. 16 No.1
dc.subjectKeywords. Automatic image annotation, region labeling, multimedia image retrieval, ground truth data creation.
dc.titleSemantic Cohesion for Image Annotation and Retrieval
dc.typeArticle


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