Hyperspectral Image Classification On Pavia
평가 지표
AA@5%perclass
Kappa@5%perclass
OA@5%perclass
Overall Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | AA@5%perclass | Kappa@5%perclass | OA@5%perclass | Overall Accuracy |
|---|---|---|---|---|
| exploring-the-relationship-between-center-and | 99.52±0.17% | 0.9957±0.0009 | 99.68±0.06% | 99.68±0.06% |
| wide-contextual-residual-network-with-active | - | - | - | 99.43% |
| hyperspectral-image-classification-of | - | - | - | - |
| adaptive-mask-sampling-and-manifold-to | - | - | - | 98.09±0.30% |
| attention-based-adaptive-spectral-spatial | - | - | - | 99.85 |
| hsi-bert-hyperspectral-image-classification | - | - | - | - |
| shorten-spatial-spectral-rnn-with-parallel | - | - | - | 98.44% |
| deep-metric-learning-based-feature-embedding | - | - | - | - |
| feature-extraction-of-hyperspectral-images | - | - | - | - |
| locality-aware-hyperspectral-classification | - | - | - | - |
| spectralnet-exploring-spatial-spectral | - | - | - | 99.99% |
| fpga-fast-patch-free-global-learning-1 | - | - | - | 99.81% |
| hyperspectral-image-classification-via-a | - | - | - | - |
| graph-information-aggregation-cross-domain | - | - | - | - |
| bass-net-band-adaptive-spectral-spatial | - | - | - | 97.48% |
| small-sample-hyperspectral-image | - | - | - | - |
| deep-supervised-learning-for-hyperspectral | - | - | - | - |
| hyperspectral-image-classification-with-1 | - | - | - | 96.18 |
| faster-hyperspectral-image-classification | - | - | - | 99.96% |
| jigsawhsi-a-network-for-hyperspectral-image | - | - | - | 100.00 |
| attention-based-second-order-pooling-network | - | - | - | 99.65% |
| generative-adversarial-networks-based-on-1 | - | - | - | - |
| hyperspectral-image-classification-using-deep | - | - | - | 99.99% |
| spectral-spatial-classification-of-2 | - | - | - | - |
| a-spectral-spatial-dependent-global-learning | - | - | - | 99.97% |
| deep-learning-for-classification-of-1 | - | - | - | 96.71 |
| generative-adversarial-networks-based-on-2 | - | - | - | - |