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Campo Dublin Core | Valor | Idioma |
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dc.contributor.author | Moreira, Gladston Juliano Prates | - |
dc.contributor.author | Luz, Eduardo José da Silva | - |
dc.contributor.author | Zanlorensi Junior, Luiz Antonio | - |
dc.contributor.author | Gomes, David Menotti | - |
dc.date.accessioned | 2018-10-16T12:55:19Z | - |
dc.date.available | 2018-10-16T12:55:19Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | MOREIRA, G. J. P. et al. Deep periocular representation aiming video surveillance. Pattern Recognition Letters, v. 114, p. 2-12, 2018. Disponível em: <https://www.sciencedirect.com/science/article/pii/S0167865517304476>. Acesso em: 16 jun. 2018. | pt_BR |
dc.identifier.issn | 01678655 | - |
dc.identifier.uri | http://www.repositorio.ufop.br/handle/123456789/10370 | - |
dc.description.abstract | Usually, in the deep learning community, it is claimed that generalized representations that yielding out- standing performance / effectiveness require a huge amount of data for learning, which directly affect biometric applications. However, recent works combining transfer learning from other domains have sur- mounted such data application constraints designing interesting and promising deep learning approaches in diverse scenarios where data is not so abundant. In this direction, a biometric system for the peri- ocular region based on deep learning approach is designed and applied on two non-cooperative ocular databases. Impressive representation discrimination is achieved with transfer learning from the facial do- main (a deep convolutional network, called VGG) and fine tuning in the specific periocular region domain. With this design, our proposal surmounts previous state-of-the-art results on NICE (mean decidability of 3.47 against 2.57) and MobBio (equal error rate of 5.42% against 8.73%) competition databases. | pt_BR |
dc.language.iso | en_US | pt_BR |
dc.rights | aberto | pt_BR |
dc.subject | Deep learning | pt_BR |
dc.subject | Transfer learning | pt_BR |
dc.subject | VGG Periocular region | pt_BR |
dc.subject | Video surveillance | pt_BR |
dc.title | Deep periocular representation aiming video surveillance. | pt_BR |
dc.type | Dissertacao | pt_BR |
dc.identifier.uri2 | https://www.sciencedirect.com/science/article/pii/S0167865517304476 | pt_BR |
Aparece nas coleções: | DECOM - Artigos publicados em periódicos |
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ARTIGO_DeepPeriocularRepresentation.pdf Restricted Access | 2,44 MB | Adobe PDF | Visualizar/Abrir |
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