Brasil
| Actas de congresos
Fast optimum-path forest classification on graphics processors
| dc.contributor | Universidade Estadual Paulista (UNESP) | |
| dc.contributor | Southwest Paulista College | |
| dc.date.accessioned | 2022-04-29T07:20:28Z | |
| dc.date.accessioned | 2022-12-20T02:31:43Z | |
| dc.date.available | 2022-04-29T07:20:28Z | |
| dc.date.available | 2022-12-20T02:31:43Z | |
| dc.date.created | 2022-04-29T07:20:28Z | |
| dc.date.issued | 2014-01-01 | |
| dc.identifier | VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, v. 2, p. 627-631. | |
| dc.identifier | http://hdl.handle.net/11449/227858 | |
| dc.identifier | 10.5220/0004740406270631 | |
| dc.identifier | 2-s2.0-84906919879 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5407993 | |
| dc.description.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. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved. | |
| dc.language | eng | |
| dc.relation | VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications | |
| dc.source | Scopus | |
| dc.subject | Graphics Processing Unit | |
| dc.subject | Optimum-Path Forest | |
| dc.title | Fast optimum-path forest classification on graphics processors | |
| dc.type | Actas de congresos |