Learning With Noisy Labels On Food 101
Metrics
Accuracy (% )
Results
Performance results of various models on this benchmark
Model Name | Accuracy (% ) | Paper Title | Repository |
|---|---|---|---|
| PSSCL | 86.41 | PSSCL: A progressive sample selection framework with contrastive loss designed for noisy labels | |
| LongReMix | 86.42 | LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment | |
| SNSCL | 86.40 | Fine-Grained Classification with Noisy Labels | - |
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