Research Article
Nested Transformers for Hyperspectral Image Classification
Table 3
Classification accuracy of different sampling rates for each dataset (%).
| | Salinas | Sampling rate | | 1% | 3% | 5% |
| | CNN | 94.34 | 96.57 | 98.93 | | ViT | 92.37 | 95.68 | 98.66 | | Swin | 95.06 | 97.73 | 98.76 | | NesT | 98.55 | 99.42 | 99.61 | | Indian Pines | Sampling rate | | 1% | 3% | 5% | | CNN | 62.14 | 75.92 | 86.75 | | ViT | 71.90 | 82.51 | 90.20 | | Swin | 64.88 | 72.87 | 75.71 | | NesT | 69.74 | 84.72 | 90.37 | | Tea Farm | Sampling rate | | 1% | 3% | 5% | | CNN | 90.06 | 96.02 | 98.39 | | ViT | 91.49 | 95.36 | 97.29 | | Swin | 94.06 | 95.49 | 96.18 | | NesT | 95.81 | 98.52 | 99.25 | | Xiongan | Sampling rate | | 1% | 3% | 5% | | CNN | 98.45 | 98.93 | 99.70 | | ViT | 98.32 | 99.42 | 99.73 | | Swin | 99.26 | 99.79 | 99.90 | | NesT | 98.31 | 99.52 | 99.80 |
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