Face Recognition On Agedb 30
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Accuracy |
|---|---|
| deep-polynomial-neural-networks | 0.98467 |
| dynamic-class-queue-for-large-scale-face | 0.9823 |
| elasticface-elastic-margin-loss-for-deep-face | 0.9835 |
| transformer-metric-loss-for-cnn-based-face | 0.9831 |