| Full text | |
| Author(s): |
Iwashita, Adriana S.
;
Papa, Joao P.
;
Falcao, Alexandre X.
;
Lotufo, Roberto A.
;
de Araujo Oliveira, Victor M.
;
Costa de Albuquerque, Victor H.
;
Tavares, Joao Manuel R. S.
;
IEEE
Total Authors: 8
|
| Document type: | Journal article |
| Source: | 2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012); v. N/A, p. 4-pg., 2012-01-01. |
| Abstract | |
In this paper we present an optimization of the Optimum-Path Forest classifier training procedure, which is based on a theoretical relationship between minimum spanning forest and optimum-path forest for a specific path-cost function. Experiments on public datasets have shown that the proposed approach can obtain similar accuracy to the traditional one hut with faster data training. (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 |