Image Classification on Stanford Cars 75%
83.13Top-1 AccuracyMGR
Evaluation results
| Method | Links | |
|---|---|---|
| MGRBackbone=ResNet18, Input Resolution=224x224, Batch size=64, Training epochs=2002023.07 | 83.13 | |
| Base ModelBackbone=ResNet18, Input Resolution=224x224, Batch size=64, Training epochs=2002023.07 | 81.68 | |
| GDA+SSLBackbone=ResNet18, Input Resolution=224x224, Batch size=64, Training epochs=2002023.07 | 81.55 | |
| GDA+MHBackbone=ResNet18, Input Resolution=224x224, Batch size=64, Training epochs=2002023.07 | 81.25 | |
| GDABackbone=ResNet18, Input Resolution=224x224, Batch size=64, Training epochs=2002023.07 | 80.67 |