Fast optimum-path forest classification on graphics processors

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorSouthwest Paulista College-
Autor(es): dc.creatorRomero, Marcos V.T.-
Autor(es): dc.creatorIwashita, Adriana S.-
Autor(es): dc.creatorPapa, Luciene P.-
Autor(es): dc.creatorSouza, André N.-
Autor(es): dc.creatorPapa, João P.-
Data de aceite: dc.date.accessioned2025-08-21T18:41:52Z-
Data de disponibilização: dc.date.available2025-08-21T18:41:52Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2014-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5220/0004740406270631-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/227858-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/227858-
Descrição: dc.descriptionSome pattern recognition techniques may present a high computational cost for learning samples' behaviour. The Optimum-Path Forest (OPF) classifier has been recently developed in order to overcome such drawbacks. Although it can achieve faster training steps when compared to some state-of-art techniques, OPF can be slower for testing in some situations. Therefore, we propose in this paper an implementation in graphics cards of the OPF classification, which showed to be more efficient than traditional OPF with similar accuracies. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.-
Descrição: dc.descriptionDepartment of Computing São Paulo State University, Bauru, São Paulo-
Descrição: dc.descriptionSouthwest Paulista College, Avaré, São Paulo-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University, Bauru, São Paulo-
Descrição: dc.descriptionDepartment of Computing São Paulo State University, Bauru, São Paulo-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University, Bauru, São Paulo-
Formato: dc.format627-631-
Idioma: dc.languageen-
Relação: dc.relationVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications-
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Palavras-chave: dc.subjectGraphics Processing Unit-
Palavras-chave: dc.subjectOptimum-Path Forest-
Título: dc.titleFast optimum-path forest classification on graphics processors-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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