| Full text | |
| Author(s): |
Maretto, Raian Vargas
;
Korting, Thales Sehn
;
Garcia Fonseca, Leila Maria
;
IEEE
Total Authors: 4
|
| Document type: | Journal article |
| Source: | 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019); v. N/A, p. 4-pg., 2019-01-01. |
| Abstract | |
Deep Learning (DL) methods are currently the state-of-the-art in Machine Learning and Pattern Recognition. In recent years, DL has been successfully applied to Remote Sensing (RS) image processing for several tasks, from pre-processing to classification. This paper presents DeepGeo, a toolbox that provides state-of-the-art DL algorithms for RS image classification and analysis. DeepGeo focuses on providing easy-to-use and extensible methods, making it easier to those RS analysts without strong programming skills. (AU) | |
| FAPESP's process: | 17/24086-2 - Management of metadata from remote sensing big data |
| Grantee: | Thales Sehn Körting |
| Support Opportunities: | Regular Research Grants |