Image Classification On Red Miniimagenet 20
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Accuracy |
|---|---|
| faster-meta-update-strategy-for-noise-robust | 51.42 |
| learning-with-neighbor-consistency-for-noisy-1 | 69.0 |
| instance-dependent-noisy-label-learning-via | 58.38 |
| instance-dependent-noisy-label-learning-via | 60.89 |
| propmix-hard-sample-filtering-and | 61.24 |