Image Classification On Eurosat
Métriques
Accuracy (%)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy (%) |
|---|---|
| mtp-advancing-remote-sensing-foundation-model | 99.24 |
| dino-mc-self-supervised-contrastive-learning | 95.7 |
| dino-mc-self-supervised-contrastive-learning | 98.78 |
| mtp-advancing-remote-sensing-foundation-model | 98.78 |
| msmatch-semi-supervised-multispectral-scene | 98.14 |
| an-evolutionary-approach-to-dynamic | 99.2 |
| a-continual-development-methodology-for-large | 99.22 |
| which-backbone-to-use-a-resource-efficient | 98.96 |
| vision-models-are-more-robust-and-fair-when | 97.5 |
| in-domain-representation-learning-for-remote-1 | 99.2 |
| mtp-advancing-remote-sensing-foundation-model | 98.76 |
| msmatch-semi-supervised-multispectral-scene | 98.65 |
| self-supervised-learning-in-remote-sensing-a | 94.4 |
| self-supervised-learning-in-remote-sensing-a | 98.9 |