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Fast Optimum-Path Forest Classification on Graphics Processors

Author(s):
Romero, Marcos V. T. ; Iwashita, Adriana S. ; Papa, Luciene P. ; Souza, Andre N. ; Papa, Joao P. ; Battiato, S ; Braz, J
Total Authors: 7
Document type: Journal article
Source: PROCEEDINGS OF THE 2014 9TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, THEORY AND APPLICATIONS (VISAPP 2014), VOL 2; v. N/A, p. 5-pg., 2014-01-01.
Abstract

Some 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. (AU)

FAPESP's process: 09/16206-1 - New trends on optimum-path forest-based pattern recognition
Grantee:João Paulo Papa
Support Opportunities: Research Grants - Young Investigators Grants
FAPESP's process: 10/12697-8 - On the Implementation of the Optimum-Path Forest Training Algorithm in GPU
Grantee:Adriana Sayuri Iwashita
Support Opportunities: Scholarships in Brazil - Master