Training Optimum-Path Forest on Graphics Processing Units
dc.contributor.author | Iwashita, Adriana S. [UNESP] | |
dc.contributor.author | Romero, Marcos V. T. [UNESP] | |
dc.contributor.author | Baldassin, Alexandro [UNESP] | |
dc.contributor.author | Costa, Kelton A. P. [UNESP] | |
dc.contributor.author | Papa, Joao P. [UNESP] | |
dc.contributor.author | Battiato, S. | |
dc.contributor.author | Braz, J. | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2019-10-04T12:30:15Z | |
dc.date.available | 2019-10-04T12:30:15Z | |
dc.date.issued | 2014-01-01 | |
dc.description.abstract | In this paper, we presented a Graphics Processing Unit (GPU)-based training algorithm for Optimum-Path Forest (OPF) classifier. The proposed approach employs the idea of a vector-matrix multiplication to speed up both traditional OPF training algorithm and a recently proposed Central Processing Unit (CPU)-based OPF training algorithm. Experiments in several public datasets have showed the efficiency of the proposed approach, which demonstrated to be up to 14 times faster for some datasets. To the best of our knowledge, this is the first GPU-based implementation for OPF training algorithm. | en |
dc.description.affiliation | Sao Paulo State Univ, Dept Comp, Bauru, SP, Brazil | |
dc.description.affiliation | Sao Paulo State Univ, Dept Stat Appl Math & Computat, Rio Claro, SP, Brazil | |
dc.description.affiliationUnesp | Sao Paulo State Univ, Dept Comp, Bauru, SP, Brazil | |
dc.description.affiliationUnesp | Sao Paulo State Univ, Dept Stat Appl Math & Computat, Rio Claro, SP, Brazil | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
dc.description.sponsorshipId | FAPESP: 2009/16206-1 | |
dc.description.sponsorshipId | FAPESP: 2010/12697-8 | |
dc.description.sponsorshipId | FAPESP: 2011/08348-0 | |
dc.description.sponsorshipId | CNPq: 470571/2013-6 | |
dc.description.sponsorshipId | CNPq: 303182/2011-3 | |
dc.format.extent | 581-588 | |
dc.identifier.citation | Proceedings Of The 2014 9th International Conference On Computer Vision, Theory And Applications (visapp 2014), Vol 2. New York: Ieee, p. 581-588, 2014. | |
dc.identifier.uri | http://hdl.handle.net/11449/184816 | |
dc.identifier.wos | WOS:000412737200071 | |
dc.language.iso | eng | |
dc.publisher | Ieee | |
dc.relation.ispartof | Proceedings Of The 2014 9th International Conference On Computer Vision, Theory And Applications (visapp 2014), Vol 2 | |
dc.rights.accessRights | Acesso aberto | |
dc.source | Web of Science | |
dc.subject | Optimum-Path Forest | |
dc.subject | Graphics Processing Unit | |
dc.title | Training Optimum-Path Forest on Graphics Processing Units | en |
dc.type | Trabalho apresentado em evento | |
dcterms.license | http://www.ieee.org/publications_standards/publications/rights/rights_policies.html | |
dcterms.rightsHolder | Ieee | |
unesp.author.lattes | 4738829911864396[3] | |
unesp.author.orcid | 0000-0001-8824-3055[3] | |
unesp.campus | Universidade Estadual Paulista (Unesp), Faculdade de Ciências, Bauru | pt |
unesp.campus | Universidade Estadual Paulista (Unesp), Instituto de Geociências e Ciências Exatas, Rio Claro | pt |
unesp.department | Computação - FCEstatística, Matemática Aplicada e Computação - IGCE | pt |