| Paper Title |
A WEAKLY-SUPERVISED CHANGE DETECTION TECHNIQUE FOR SAR IMAGES BASED ON DEEP LEARNING AND SYNTHETIC TRAINING DATA GENERATED BY AN ENSEMBLE OF SELF-ORGANIZING MAPS |
| Paper Identifier | MOP2.PK.11 |
|---|
| Authors |
Victor-Emil Neagoe, Adrian-Dumitru Ciotec, Polytechnic University of Bucharest, Romania; Lorenzo Bruzzone, University of Trento, Italy |
| Session |
Analysis of Image Time Series II |
| Location |
Room 501-502: Poster Area K |
| Session Time |
Monday, 29 July, 15:20 - 16:20 |
| Presentation Time |
Monday, 29 July, 15:20 - 16:20 |
| Presentation Mode |
Poster
|
| Topic |
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR): Change Detection and Multi-Temporal Analysis
|
