Semantic Segmentation On Lombardia Sentinel 2
Metrics
Overall Accuracy
Results
Performance results of various models on this benchmark
Model Name | Overall Accuracy | Paper Title | Repository |
|---|---|---|---|
| UNet3D | 80.77 | Enhancing crop segmentation in satellite image time-series with transformer networks | |
| DeepLabv3 3D | 74.51 | Enhancing crop segmentation in satellite image time-series with transformer networks | |
| Swin UNETR | 79.64 | Enhancing crop segmentation in satellite image time-series with transformer networks | |
| 3D FPN with NDVI Loss | 77.23 | Enhancing crop segmentation in satellite image time-series with transformer networks |
0 of 4 row(s) selected.