| Full text | |
| Author(s): |
Pisani, R.
;
Riedel, P.
;
Gomes, A.
;
Mizobe, R.
;
Papa, J.
;
IEEE
Total Authors: 6
|
| Document type: | Journal article |
| Source: | 2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS); v. N/A, p. 4-pg., 2011-01-01. |
| Abstract | |
In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. (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 |