Image Classification On Red Miniimagenet 40
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy | Paper Title | Repository |
|---|---|---|---|
| FaMUS | 48.06 | Faster Meta Update Strategy for Noise-Robust Deep Learning | |
| InstanceGM-SS | 56.37 | Instance-Dependent Noisy Label Learning via Graphical Modelling | |
| NCR (ResNet-18) | 64.6 | Learning with Neighbor Consistency for Noisy Labels | |
| InstanceGM | 52.24 | Instance-Dependent Noisy Label Learning via Graphical Modelling | |
| PropMix | 56.22 | PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels |
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