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Restricted Boltzmann Machines for Gender Classification

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Restricted Boltzmann Machines for Gender Classification

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dc.contributor.author Mansanet Sandín, Jorge es_ES
dc.contributor.author Albiol Colomer, Alberto es_ES
dc.contributor.author Paredes Palacios, Roberto es_ES
dc.contributor.author Villegas, Mauricio es_ES
dc.contributor.author Albiol Colomer, Antonio José es_ES
dc.date.accessioned 2015-09-09T09:41:02Z
dc.date.available 2015-09-09T09:41:02Z
dc.date.issued 2014-10-10
dc.identifier.issn 0302-9743
dc.identifier.uri http://hdl.handle.net/10251/54425
dc.description.abstract This paper deals with automatic feature learning using a generative model called Restricted Boltzmann Machine (RBM) for the problem of gender recognition in face images. The RBM is presented together with some practical learning tricks to improve the learning capabilities and speedup the training process. The performance of the features obtained is compared against several linear methods using the same dataset and the same evaluation protocol. The results show a classification accuracy improvement compared with classical linear projection methods. Moreover, in order to increase even more the classification accuracy, we have run some experiments where an SVM is fed with the non-linear mapping obtained by the RBM in a tandem configuration. es_ES
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Lecture Notes in Computer Science es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Representation learning es_ES
dc.subject RBM es_ES
dc.subject Gender classification es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.subject.classification TEORIA DE LA SEÑAL Y COMUNICACIONES es_ES
dc.title Restricted Boltzmann Machines for Gender Classification es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/978-3-319-11758-4_30
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Mansanet Sandin, J.; Albiol Colomer, A.; Paredes Palacios, R.; Villegas, M.; Albiol Colomer, AJ. (2014). Restricted Boltzmann Machines for Gender Classification. Lecture Notes in Computer Science. 8814:274-281. doi:10.1007/978-3-319-11758-4_30 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/978-3-319-11758-4_30 es_ES
dc.description.upvformatpinicio 274 es_ES
dc.description.upvformatpfin 281 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 8814 es_ES
dc.relation.senia 281672 es_ES
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