Unsupervised Image Classification On Stl 10
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Accuracy |
|---|---|
| Modell 1 | 90.8 |
| learning-to-classify-images-without-labels | 80.90 |
| invariant-information-distillation-for | 61.00 |
| mv-mr-multi-views-and-multi-representations | 89.67 |
| ipcl-iterative-pseudo-supervised-contrastive | - |
| scatsimclr-self-supervised-contrastive | 85.11 |
| mitigating-embedding-and-class-assignment | 66.50 |
| let-go-of-your-labels-with-unsupervised-1 | 99.7 |
| improving-unsupervised-image-clustering-with | 86.7 |