Semi Supervised Image Classification On Cifar 7
Metriken
Percentage error
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Percentage error |
|---|---|
| semantic-aware-representation-learning-via-1 | 5.88±1.19 |
| np-match-when-neural-processes-meet-semi | 4.91 |
| relationmatch-matching-in-batch-relationships | 4.96 |
| flexmatch-boosting-semi-supervised-learning | 4.99±0.16 |
| fixmatch-simplifying-semi-supervised-learning | 11.39±3.35 |
| remixmatch-semi-supervised-learning-with-1 | 19.10 |
| boosting-the-performance-of-semi-supervised | 7.39±0.61 |
| selfmatch-combining-contrastive-self | 6.81±1.08 |
| doublematch-improving-semi-supervised | 13.59±5.60 |
| mutexmatch-semi-supervised-learning-with-1 | 5.79 |
| simmatch-semi-supervised-learning-with | 5.6 |
| dp-ssl-towards-robust-semi-supervised | 6.54±0.98 |
| debiased-learning-from-naturally-imbalanced | 5.4 |
| freematch-self-adaptive-thresholding-for-semi | 4.9 |
| shrinking-class-space-for-enhanced-certainty | 5.08 |
| unsupervised-learning-using-pretrained-cnn | 16.90 |
| contrastive-regularization-for-semi | 5.69 |
| comatch-semi-supervised-learning-with | 6.91±1.39 |