Hyperspectral Image Classification on Pavia University
100Overall Accuracy (OA)STNet
Evaluation results
| Method | Links | ||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| STNet2025.06 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| WCNet2025.04 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DSXFormer2026.02 | 99.85 | — | — | — | — | — | — | — | — | — | 99.7 | 99.8 | — | 100 | 99.99 | 99.73 | 98.32 | 100 | 100 | 99.89 | 100 | 99.4 | — | — | — | — | |
| 3D-CNN2025.06 | 99.79 | 99.96 | 99.99 | 99.64 | 99.83 | 99.81 | 99.98 | 97.97 | 99.56 | 100 | 99.75 | 99.87 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| 3D-SE-DenseNet2025.06 | 99.48 | 99.32 | 99.87 | 96.76 | 99.23 | 99.64 | 99.8 | 99.47 | 99.32 | 100 | 99.16 | 99.31 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SwinT2026.02 | 99.41 | — | — | — | — | — | — | — | — | — | 98.45 | 99.22 | — | 99.36 | 99.81 | 98.85 | 98.8 | 97.21 | 99.94 | 98.83 | 98.73 | 98.85 | — | — | — | — | |
| PyFormer2026.02 | 99.06 | — | — | — | — | — | — | — | — | — | 98.57 | 98.75 | — | 99.26 | 100 | 98.03 | 97.43 | 100 | 99.76 | 100 | 94.39 | 98.31 | — | — | — | — | |
| PMCN2026.02 | 99.04 | — | — | — | — | — | — | — | — | — | 98.57 | 98.73 | — | 99.4 | 100 | 96.32 | 97.78 | 100 | 99.79 | 100 | 94.31 | 99.58 | — | — | — | — | |
| WaveFormer2026.02 | 98.9 | — | — | — | — | — | — | — | — | — | 98.33 | 98.54 | — | 99.03 | 100 | 96.95 | 97.61 | 100 | 99.71 | 100 | 93.52 | 98.17 | — | — | — | — | |
| FADCNN2026.02 | 98.87 | — | — | — | — | — | — | — | — | — | 98.05 | 95.25 | — | 99.7 | 99.75 | 94.31 | 99.1 | 99.82 | 99.92 | 96.97 | 97.9 | 98.97 | — | — | — | — | |
| St-SS-pGRUArchitecture=parallel2018.10 | 98.44 | — | — | — | — | — | — | — | — | — | — | — | 128.91 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MixerCAParameters=59,889, FLOPs=19,145,472, MACs=9,318,1442026.04 | 97.81 | 96.06 | 99.84 | 82.47 | 96.57 | 98.96 | 99.98 | 99.77 | 97.42 | 93.66 | 96.25 | 97.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| St-SS-GRU2018.10 | 96.8 | — | — | — | — | — | — | — | — | — | — | — | 104.56 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Tri-CNNParameters=130,222,665, FLOPs=260,116,992, MACs=130,058,4962026.04 | 95.87 | 93.24 | 100 | 81.85 | 92.89 | 99.93 | 93.8 | 92.41 | 92.1 | 98.31 | 94.04 | 94.5 | — | — | — | — | — | — | — | — | — | — | — | — | 4.43 | 0.0011 | |
| HybridnSNParameters=2,313,465, FLOPs=97,483,008, MACs=48,741,5042026.04 | 95.65 | 98.25 | 99.91 | 90 | 85.87 | 98.88 | 92.34 | 98.27 | 84.71 | 89.55 | 93.34 | 94.19 | — | — | — | — | — | — | — | — | — | — | — | — | 4.41 | 0.0012 | |
| DE-CFFNParameters (M)=0.257, Memory (MB)=0.98, Inference Time (ms)=12.152026.06 | 95.17 | — | — | — | — | — | — | — | — | — | 92.32 | 93.54 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| 3D-CNNParameters=73,417, FLOPs=35,493, MACs=16,9602026.04 | 94.68 | 94.45 | 99.1 | 88.42 | 90.54 | 99.93 | 90.4 | 99.47 | 83.98 | 86.59 | 92.76 | 92.93 | — | — | — | — | — | — | — | — | — | — | — | — | 4.91 | 0.0065 | |
| CFFNParameters (M)=0.924, Memory (MB)=3.52, Inference Time (ms)=11.722026.06 | 94.35 | — | — | — | — | — | — | — | — | — | 92.88 | 92.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| VIT2026.02 | 93.31 | — | — | — | — | — | — | — | — | — | 85.96 | 91.1 | — | 87.64 | 98.7 | 86.5 | 80.73 | 85.87 | 99.06 | 93.28 | 84.89 | 88.31 | — | — | — | — | |
| PMI-CNNParameters=3,779,593, FLOPs=104,416,512, MACs=52,208,2562026.04 | 93.29 | 91.13 | 99.1 | 62.08 | 91.29 | 89.89 | 96.12 | 97.97 | 83.27 | 91.66 | 89.58 | 91.07 | — | — | — | — | — | — | — | — | — | — | — | — | 7.06 | 0.0038 | |
| SSRN2025.06 | 92.99 | 89.93 | 86.48 | 99.95 | 95.78 | 97.69 | 95.44 | 84.4 | 100 | 87.24 | 87.21 | 90.58 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| St-GRU2018.10 | 92.25 | — | — | — | — | — | — | — | — | — | — | — | 7.31 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Hit2025.06 | 92 | 96.19 | 92.79 | 93.21 | 97.33 | 99.96 | 99.91 | 98.22 | 99.15 | 99.77 | 93.24 | 89.77 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Swin T.Parameters=140,425, FLOPs=3,568,712, MACs=1,659,8322026.04 | 91.96 | 93.26 | 98.69 | 74.94 | 80.29 | 96.73 | 87.97 | 98.05 | 80.66 | 75.71 | 87.83 | 89.27 | — | — | — | — | — | — | — | — | — | — | — | — | 11.45 | 0.0035 | |
| ViTParameters=7,499,977, FLOPs=13,765,120, MACs=6,845,6962026.04 | 91.76 | 89.37 | 99.79 | 71.46 | 87.83 | 98.14 | 84.41 | 89.4 | 80.39 | 85.64 | 87.82 | 89 | — | — | — | — | — | — | — | — | — | — | — | — | 10.03 | 0.0017 | |
| Spectralformer2025.06 | 91.07 | 82.73 | 94.03 | 73.66 | 93.75 | 99.28 | 90.75 | 87.56 | 95.81 | 94.21 | 90.2 | 88.05 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Spectralformer2025.04 | 91.07 | 82.73 | 94.03 | 73.66 | 93.75 | 99.28 | 90.75 | 87.56 | 95.81 | 94.21 | 90.2 | 88.05 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| 2D-CNNParameters=83,401, FLOPs=4,846,144, MACs=2,419,2002026.04 | 90.67 | 93.7 | 99.46 | 74.37 | 89.88 | 99.03 | 72.1 | 94.14 | 73.19 | 84.9 | 87.14 | 87.44 | — | — | — | — | — | — | — | — | — | — | — | — | 10.89 | 0.0088 | |
| NL-GCNN2026.02 | 90.04 | — | — | — | — | — | — | — | — | — | 90.87 | 87.06 | — | 86.8 | 88.74 | 70.84 | 98.43 | 99.85 | 94.37 | 86.24 | 96.74 | 95.78 | — | — | — | — | |
| GCNN2026.02 | 87.08 | — | — | — | — | — | — | — | — | — | 86.71 | 83.07 | — | 78.89 | 90.5 | 71.7 | 98.76 | 99.93 | 79.08 | 71.2 | 92.83 | 97.47 | — | — | — | — | |
| 2D CNN2026.02 | 86.93 | — | — | — | — | — | — | — | — | — | 85.38 | 82.42 | — | 83.85 | 96.09 | 81.47 | 96.12 | 98.74 | 49.79 | 79.32 | 88.89 | 94.19 | — | — | — | — | |
| GRU2018.10 | 86.92 | — | — | — | — | — | — | — | — | — | — | — | 232.15 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SVM2026.04 | 86.13 | 82.97 | 93.06 | 60.41 | 85.31 | 99.55 | 77.99 | 75.34 | 78.63 | 100 | 83.94 | 81.57 | — | — | — | — | — | — | — | — | — | — | — | — | 11.73 | 0.0068 | |
| MLPParameters=137,993, FLOPs=274,432, MACs=137,2162026.04 | 84.88 | 88.22 | 97.25 | 59.17 | 82.87 | 95.46 | 66.06 | 47.44 | 65.64 | 93.56 | 78.05 | 79.56 | — | — | — | — | — | — | — | — | — | — | — | — | 15.24 | 0.0057 | |
| LSTM2018.10 | 84.68 | — | — | — | — | — | — | — | — | — | — | — | 434.22 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CCF-2002026.02 | 83.36 | — | — | — | — | — | — | — | — | — | 90.26 | 79.05 | — | 86.59 | 72.33 | 71.75 | 99.09 | 99.78 | 97.26 | 91.88 | 94.92 | 98.73 | — | — | — | — | |
| SVM-RBF2026.02 | 78.89 | — | — | — | — | — | — | — | — | — | 87.95 | 74.91 | — | 82.37 | 67.87 | 69.18 | 98.37 | 99.41 | 93.64 | 91.2 | 92.59 | 96.94 | — | — | — | — | |
| 3D-CNN2025.04 | — | 99.96 | 99.99 | 99.64 | 99.83 | 99.81 | 99.98 | 97.97 | 99.56 | 100 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| 3D-SE-DenseNet2025.04 | — | 99.32 | 99.87 | 96.76 | 99.23 | 99.64 | 99.8 | 99.47 | 99.32 | 100 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BCSCPerformance=Best case2026.03 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 47 | — | — | |
| FCM2026.01 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 2,348.66 | — | — | — | |
| k-means2026.01 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 2.23 | — | — | — | |
| KNN2026.01 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 1.62 | — | — | — | |
| LGCNet2025.04 | — | 100 | 100 | 99.88 | 100 | 100 | 100 | 100 | 100 | 100 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Ours-G2026.01 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 133.52 | — | — | — | |
| Ours-O2026.01 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 485.31 | — | — | — | |
| RF2026.01 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 50.04 | — | — | — | |
| SSRN2025.04 | — | 89.93 | 86.48 | 99.95 | 95.78 | 97.69 | 95.44 | 84.4 | 100 | 87.24 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SVM2026.01 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 0.63 | — | — | — | |
| UBCSCPerformance=Best case2026.03 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 63 | — | — |