Semantic Segmentation On Lombardia Sentinel 2
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Overall Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | 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 |
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