Rice
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Remote Sensing Image Dehazing (RSI Dehazing) | RICE1 | PSNR35.92 | 30 | |
| Genomic Prediction | Rice dataset | Rank1 | 27 | |
| Organ-level semantic segmentation | Rice | Green Veg IoU87.11 | 18 | |
| Classification | Rice | AUC0.977 | 18 | |
| Execution time measurement | Rice 50% MNAR | Training Time (s)0.171 | 15 | |
| Node Classification | Rice31 | Accuracy87.55 | 14 | |
| Plant-level segmentation | Rice | Crop mIoU86.8 | 8 | |
| Declouding | RICE 2 | PSNR36.35 | 7 | |
| Transductive Node Classification | Rice31 | Accuracy87.89 | 7 | |
| Classification | rice UCI (test) | Accuracy91.9 | 6 | |
| Manifold Learning | Rice Cammeo and Osmancik | (TW + CN)/299.11 | 5 | |
| Binary Classification | Rice (test) | Macro F1-Score92.7 | 5 | |
| Subspecies Generalization | Rice glaberrima subspecies Far-OOD | Accuracy59.9 | 3 | |
| Subspecies Generalization | Rice barthii subspecies Far-OOD | Accuracy60.8 | 3 | |
| Subspecies Generalization | Rice rufipogon subspecies Mid-OOD | Accuracy63.9 | 3 | |
| Subspecies Generalization | Rice aus subspecies Near-OOD | Accuracy55.6 | 3 | |
| Subspecies Generalization | Rice japonica subspecies In-Domain | Accuracy59 | 3 |
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