Image Classification On Emnist Letters
Metriken
Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Accuracy |
|---|---|
| efficient-neural-vision-systems-based-on | 93.65 |
| emnist-an-extension-of-mnist-to-handwritten | 55.78 |
| spinalnet-deep-neural-network-with-gradual-1 | 95.86 |
| regularizing-cross-entropy-loss-via-minimum | 95.928 |
| a-continual-development-methodology-for-large | 95.03 |
| handwritten-digit-and-letter-recognition | 89.51 |
| emnist-an-extension-of-mnist-to-handwritten | 85.27 |
| wavemix-lite-a-resource-efficient-neural | 95.96 |
| textcaps-handwritten-character-recognition | 95.39 |
| spinalnet-deep-neural-network-with-gradual-1 | 95.88 |
| regularizing-cross-entropy-loss-via-minimum | 95.933 |