Crop Classification On Cropharvest Kenya
Metriken
Average Accuracy
F1 Macro
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | |||
|---|---|---|---|
| Radar TS with TempCNN | 0.676 | 0.684 | In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data |
| Input Fusion with TAE | 0.673 | 0.672 | In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data |
| Gated Fusion (Feature-level) | 0.665 | - | A Comparative Assessment of Multi-view fusion learning for Crop Classification |
| Feature-level fusion (sum) | 0.630 | - | A Comparative Assessment of Multi-view fusion learning for Crop Classification |
| PrestoR - no DW | - | - | Lightweight, Pre-trained Transformers for Remote Sensing Timeseries |
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