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Fast optimum-path forest classification on graphics processors

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dc.contributor.authorRomero, Marcos V.T. [UNESP]
dc.contributor.authorIwashita, Adriana S. [UNESP]
dc.contributor.authorPapa, Luciene P.
dc.contributor.authorSouza, André N. [UNESP]
dc.contributor.authorPapa, João P. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionSouthwest Paulista College
dc.date.accessioned2022-04-29T07:20:28Z
dc.date.available2022-04-29T07:20:28Z
dc.date.issued2014-01-01
dc.description.abstractSome 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.en
dc.description.affiliationDepartment of Computing São Paulo State University, Bauru, São Paulo
dc.description.affiliationSouthwest Paulista College, Avaré, São Paulo
dc.description.affiliationDepartment of Electrical Engineering São Paulo State University, Bauru, São Paulo
dc.description.affiliationUnespDepartment of Computing São Paulo State University, Bauru, São Paulo
dc.description.affiliationUnespDepartment of Electrical Engineering São Paulo State University, Bauru, São Paulo
dc.format.extent627-631
dc.identifierhttp://dx.doi.org/10.5220/0004740406270631
dc.identifier.citationVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, v. 2, p. 627-631.
dc.identifier.doi10.5220/0004740406270631
dc.identifier.scopus2-s2.0-84906919879
dc.identifier.urihttp://hdl.handle.net/11449/227858
dc.language.isoeng
dc.relation.ispartofVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
dc.sourceScopus
dc.subjectGraphics Processing Unit
dc.subjectOptimum-Path Forest
dc.titleFast optimum-path forest classification on graphics processorsen
dc.typeTrabalho apresentado em evento
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt
unesp.departmentEngenharia Elétrica - FEBpt

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Bauru - FC - Faculdade de Ciências
Bauru - FEB - Faculdade de Engenharia