Change Detection On Dsifn Cd
Métriques
F1
IoU
KC
Overall Accuracy
Precision
Recall
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | F1 | IoU | KC | Overall Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|
| c2f-semicd-a-coarse-to-fine-semi-supervised | 64.03 | 47.09 | 55.62 | 86.19 | 57.45 | 72.31 |
| hcgmnet-a-hierarchical-change-guiding-map | 55.00 | 37.93 | 41.53 | 76.26 | 40.57 | 85.35 |
| ultralightweight-spatial-spectral-feature | 69.47 | 53.21 | - | - | - | - |
| hanet-a-hierarchical-attention-network-for | 62.67 | 45.64 | 54.01 | 85.76 | 56.52 | 70.33 |
| change-guiding-network-incorporating-change | 60.19 | 43.05 | 49.34 | 81.71 | 47.75 | 81.38 |
| rethinking-remote-sensing-change-detection | 74.75 | 59.68 | - | 91.55 | 75.96 | 73.57 |
| remote-sensing-change-detection-segmentation | 96.65 | - | - | 97.09 | - | - |
| saras-net-scale-and-relation-aware-siamese | 67.58 | 51.04 | - | 89.01 | - | - |
| frequency-temporal-attention-network-for-1 | 89.56 | 81.10 | - | - | 90.54 | 88.61 |