Semantic Segmentation On Isprs Vaihingen
Métriques
Average F1
Overall Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Average F1 | Overall Accuracy |
|---|---|---|
| semantic-labeling-of-high-resolution-images | 93.7 | 91.8 |
| efficient-hybrid-transformer-learning-global | 90.4 | 91.0 |
| abcnet-attentive-bilateral-contextual-network | - | 90.7 |
| lsknet-a-foundation-lightweight-backbone-for | 91.7 | 93.6 |
| transformer-meets-convolution-a-bilateral | - | 90.5 |
| sfa-net-semantic-feature-adjustment-network | 91.2 | - |
| lsknet-a-foundation-lightweight-backbone-for | 91.8 | 93.6 |
| transformer-meets-dcfam-a-novel-semantic | 90.7 | 91.6 |
| efficient-hybrid-transformer-learning-global | 91.3 | 91.6 |
| stochastic-subsampling-with-average-pooling | - | 90.14 |
| multiattention-network-for-semantic | - | 90.963 |