Image Classification On Cifar 10 With Noisy
Metrics
Accuracy (under 20% Sym. label noise)
Accuracy (under 50% Sym. label noise)
Accuracy (under 80% Sym. label noise)
Accuracy (under 90% Sym. label noise)
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy (under 20% Sym. label noise) | Accuracy (under 50% Sym. label noise) | Accuracy (under 80% Sym. label noise) | Accuracy (under 90% Sym. label noise) |
|---|---|---|---|---|
| s3-supervised-self-supervised-learning-under-1 | 96.74% | 96.13% | 95.56% | 95.17% |
| sample-prior-guided-robust-model-learning-to | 96.7% | 96.3% | 94.7% | 84.0% |
| contrast-to-divide-self-supervised-pre-1 | 96.23 ± 0.09 | 95.15 ± 0.16 | 94.30 ± 0.12 | 93.42 ± 0.09 |
| contrast-to-divide-self-supervised-pre-1 | 96.74 ± 0.12 | 95.55 ± 0.32 | 93.11 ± 0.70 | 89.30 ± 0.21 |