Human face verification based on multidimensional polynomial powers of sigmoid (PPS)

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorLisbon University-
Autor(es): dc.creatorMarar, João Fernando-
Autor(es): dc.creatorCoelho, Helder-
Data de aceite: dc.date.accessioned2025-08-21T15:14:51Z-
Data de disponibilização: dc.date.available2025-08-21T15:14:51Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2008-12-17-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/225358-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/225358-
Descrição: dc.descriptionIn this paper, we described how a multidimensional wavelet neural networks based on Polynomial Powers of Sigmoid (PPS) can be constructed, trained and applied in image processing tasks. In this sense, a novel and uniform framework for face verification is presented. The framework is based on a family of PPS wavelets,generated from linear combination of the sigmoid functions, and can be considered appearance based in that features are extracted from the face image. The feature vectors are then subjected to subspace projection of PPS-wavelet. The design of PPS-wavelet neural networks is also discussed, which is seldom reported in the literature. The Stirling Universitys face database were used to generate the results. Our method has achieved 92 % of correct detection and 5 % of false detection rate on the database.-
Descrição: dc.descriptionDepartment of Computing Adaptive Systems and Computational Intelligence Laboratory São Paulo State University, Bauru , São Paulo-
Descrição: dc.descriptionDepartment of Informatics Laboratory of Agent Modelling Lisbon University, Lisbon-
Descrição: dc.descriptionDepartment of Computing Adaptive Systems and Computational Intelligence Laboratory São Paulo State University, Bauru , São Paulo-
Formato: dc.format99-106-
Idioma: dc.languageen-
Relação: dc.relationHEALTHINF 2008 - 1st International Conference on Health Informatics, Proceedings-
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Palavras-chave: dc.subjectActivation functions-
Palavras-chave: dc.subjectArtificial neural network-
Palavras-chave: dc.subjectFeedforward networks-
Palavras-chave: dc.subjectHuman face verification-
Palavras-chave: dc.subjectPolynomial powers of sigmoid (PPS)-
Palavras-chave: dc.subjectPps-wavelet neural networks-
Palavras-chave: dc.subjectWavelets functions-
Título: dc.titleHuman face verification based on multidimensional polynomial powers of sigmoid (PPS)-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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