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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.date.accessioned | 2017-07-10T09:42:07Z | |
dc.date.available | 2017-07-10T09:42:07Z | |
dc.date.issued | 2016-01-15 | |
dc.identifier.issn | 0167-8655 | |
dc.identifier.uri | http://hdl.handle.net/10251/84826 | |
dc.description.abstract | Deep learning methods are able to automatically discover better representations of the data to improve the performance of the classifiers. However, in computer vision tasks, such as the gender recognition problem, sometimes it is difficult to directly learn from the entire image. In this work we propose a new model called Local Deep Neural Network (Local-DNN), which is based on two key concepts: local features and deep architectures. The model learns from small overlapping regions in the visual field using discriminative feed forward networks with several layers. We evaluate our approach on two well-known gender benchmarks, showing that our Local-DNN outperforms other deep learning methods also evaluated and obtains state-of-the-art results in both benchmarks. (C) 2015 Elsevier B.V. All rights reserved. | es_ES |
dc.description.sponsorship | This work was financially supported by the Ministerio de Ciencia e Innovacin (Spain), Plan Nacional de I-D+i, TEC2009-09146, and the FPI grant BES-2010-032945. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Pattern Recognition Letters | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Gender recognition | es_ES |
dc.subject | Face analysis | es_ES |
dc.subject | Deep learning | es_ES |
dc.subject | Local Deep Neural Network | es_ES |
dc.subject.classification | LENGUAJES Y SISTEMAS INFORMATICOS | es_ES |
dc.subject.classification | TEORIA DE LA SEÑAL Y COMUNICACIONES | es_ES |
dc.title | Local Deep Neural Networks for gender recognition | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.patrec.2015.11.015 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//TEC2009-09146/ES/Nuevas Tecnicas Para Video Vigilancia Inteligente/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//BES-2010-032945/ES/BES-2010-032945/ | es_ES |
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. Escola Tècnica Superior d'Enginyeria Informàtica | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Telecomunicación - Escola Tècnica Superior d'Enginyers de Telecomunicació | es_ES |
dc.description.bibliographicCitation | Mansanet Sandín, J.; Albiol Colomer, A.; Paredes Palacios, R. (2016). Local Deep Neural Networks for gender recognition. Pattern Recognition Letters. 70:80-86. https://doi.org/10.1016/j.patrec.2015.11.015 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1016/j.patrec.2015.11.015 | es_ES |
dc.description.upvformatpinicio | 80 | es_ES |
dc.description.upvformatpfin | 86 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 70 | es_ES |
dc.relation.senia | 328060 | es_ES |