Hyperspectral Image Classification on Xuzhou
99.16Class 1 AccuracyMixerCA
Evaluation Results
| Method | Links | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MixerCA2026.04 | 99.16 | 99.18 | 98.96 | 98.14 | 98.56 | 99.67 | 99.64 | 99.87 | 95.34 | 99.2 | 98.77 | 99.14 | — | — | |
| 3D-CNN2026.04 | 98.14 | 99.03 | 88.14 | 95.86 | 95.81 | 97.37 | 94.55 | 97.91 | 93.97 | 95.73 | 95.65 | 95.25 | 7.88 | 3.4 | |
| HybridnSN2026.04 | 98.01 | 99.08 | 96.51 | 97.53 | 99.07 | 95.32 | 98.21 | 100 | 93.78 | 97.38 | 97.49 | 97.08 | 5.32 | 8.57 | |
| PMI-CNN2026.04 | 97.73 | 99.6 | 98.02 | 97.62 | 95.76 | 97.37 | 98.96 | 99 | 96.19 | 95.53 | 97.58 | 95.01 | 8.56 | 1.25 | |
| ViT2026.04 | 97.53 | 98.51 | 98.92 | 91.41 | 98.38 | 90.76 | 90.77 | 99.12 | 96.64 | 94.6 | 95.66 | 94 | 11.49 | 2.77 | |
| Tri-CNN2026.04 | 97 | 98.78 | 97.31 | 91.41 | 99.68 | 85.34 | 98.78 | 97.8 | 94.46 | 94.78 | 95.53 | 94.18 | 11.12 | 3.92 | |
| Swin T.2026.04 | 96.72 | 98.76 | 95.65 | 94.99 | 98.17 | 96.39 | 98.51 | 99.39 | 95.24 | 95.23 | 97.09 | 94.69 | 10.59 | 4.72 | |
| MLP2026.04 | 94.72 | 97.29 | 86.92 | 85.86 | 93.7 | 70.94 | 84.59 | 90.94 | 93.62 | 90.43 | 88.9 | 89.34 | 18.02 | 6.1 | |
| SVM2026.04 | 93.93 | 97.77 | 77.87 | 86.98 | 93.45 | 64.78 | 77.35 | 95.81 | 97.33 | 88.57 | 87.38 | 87.27 | 23.99 | 8.66 | |
| 2D-CNN2026.04 | 89.42 | 97.99 | 91.88 | 95.28 | 99.36 | 92.73 | 96.22 | 89.28 | 95.67 | 92.64 | 94.05 | 91.8 | 12.63 | 4.62 |