Image Classification On Red Miniimagenet 80
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Accuracy |
|---|---|
| instance-dependent-noisy-label-learning-via | 39.62 |
| propmix-hard-sample-filtering-and | 43.42 |
| faster-meta-update-strategy-for-noise-robust | 35.5 |
| instance-dependent-noisy-label-learning-via | 44.03 |
| learning-with-neighbor-consistency-for-noisy-1 | 51.2 |