ENHANCING THE QUALITY OF CNN-BASED BURNED AREA DETECTION IN SATELLITE IMAGERY THROUGH DATA AUGMENTATION
This study aims to enhance the quality of detecting burned areas in satellite imagery using deep learning by optimizing the training dataset volume through the application of various augmentation methods. The study analyzes the impact of image flipping, rotation, and noise addition on the overall ac...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-12-01
|
| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1749/2023/isprs-archives-XLVIII-1-W2-2023-1749-2023.pdf |