Classification on Augsburg Dataset
98.1Accuracy (Forest)S2ENet
Evaluation results
| Method | Links | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| S2ENet2026.04 | 98.1 | 99.08 | 12.19 | 91.78 | 45.12 | 1.22 | 24.09 | 88.22 | 53.08 | 0.8647 | |
| MACN2026.04 | 97.95 | 98.68 | 45.3 | 94.24 | 51.24 | 6.74 | 49.27 | 91.18 | 63.35 | 0.8723 | |
| HCT2026.04 | 96.92 | 98.96 | 33.05 | 92.36 | 54.11 | 6.62 | 4.74 | 89.83 | 61.34 | 0.8528 | |
| MGMNet2026.04 | 96.28 | 97.76 | 49.61 | 92.32 | 56.6 | 5.15 | 49.93 | 90.1 | 63.95 | 0.8575 | |
| CHNet2026.04 | 96.24 | 99.22 | 44.23 | 93.83 | 54.68 | 19.85 | 46.74 | 91.14 | 64.97 | 0.871 | |
| RSCNet2026.04 | 96.07 | 96.4 | 78.38 | 94.08 | 58.32 | 1.96 | 50.07 | 91.5 | 67.89 | 0.8776 | |
| AsyFFNet2026.04 | 96.01 | 97.96 | 53.29 | 91.74 | 65.39 | 4.58 | 49.64 | 90.15 | 65.51 | 0.8574 | |
| MICF-Net2026.04 | 95.98 | 98.46 | 58.38 | 91.75 | 40.73 | 23.53 | 44.81 | 90.74 | 64.81 | 0.8665 | |
| GCCQTNet2026.04 | 95.26 | 96.8 | 68.2 | 91.52 | 41.68 | 13.97 | 46.8 | 90.22 | 64.89 | 0.86 | |
| FusAtNet2026.04 | 93.78 | 97.58 | 26.48 | 97.67 | 52.77 | 24.66 | 47.51 | 90.62 | 62.92 | 0.8633 | |
| ExViT2026.04 | 90.04 | 95.44 | 34.58 | 90.68 | 51.82 | 28.63 | 17.65 | 86.65 | 58.4 | 0.8079 |