Image Classification On Food 101N 1
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Accuracy | Paper Title | Repository |
|---|---|---|---|
| LRA-diffusion (CLIP ViT) | 93.42 | Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels | |
| CleanNet | 90.39 | CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise | |
| LongReMix | 87.39% | LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment | |
| SURE(ResNet-50) | 88.0 | SURE: SUrvey REcipes for building reliable and robust deep networks |
0 of 4 row(s) selected.