Image Classification On Food 101N 1
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| 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 |
| SURE(ResNet-50) | 88.0 | SURE: SUrvey REcipes for building reliable and robust deep networks |
| LongReMix | 87.39% | LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment |
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