Fine Grained Image Classification On Foodx
Métriques
Accuracy (%)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy (%) | Paper Title | Repository |
|---|---|---|---|
| VOLO-D5 | 79.15 | Learning Multi-Subset of Classes for Fine-Grained Food Recognition | |
| CSWin-L | 79.90 | Learning Multi-Subset of Classes for Fine-Grained Food Recognition |
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