Image Classification on MURA Fracture
90.6AccuracyMedDiffuseMix
Evaluation results
| Method | Links | |
|---|---|---|
| MedDiffuseMixModel=EfficientNet-B42026.06 | 90.6 | |
| MedDiffuseMixModel=Swin-T2026.06 | 89.7 | |
| MedDiffuseMixModel=DenseNet-1212026.06 | 89.5 | |
| DBAModel=EfficientNet-B42026.06 | 88.9 | |
| SaliencyMixModel=EfficientNet-B42026.06 | 88.6 | |
| MedDiffuseMixModel=ResNet-502026.06 | 88.4 | |
| GenMixModel=EfficientNet-B42026.06 | 88.3 | |
| DBAModel=Swin-T2026.06 | 88.2 | |
| DBAModel=DenseNet-1212026.06 | 88 | |
| MedDiffuseMixModel=ViT-B/162026.06 | 88 | |
| SaliencyMixModel=Swin-T2026.06 | 87.9 | |
| MixupModel=EfficientNet-B42026.06 | 87.8 | |
| SaliencyMixModel=DenseNet-1212026.06 | 87.7 | |
| GenMixModel=Swin-T2026.06 | 87.6 | |
| GenMixModel=DenseNet-1212026.06 | 87.4 | |
| Standard AugModel=EfficientNet-B42026.06 | 87.3 | |
| MixupModel=Swin-T2026.06 | 87.2 | |
| DBAModel=ResNet-502026.06 | 87 | |
| MixupModel=DenseNet-1212026.06 | 87 | |
| SaliencyMixModel=ResNet-502026.06 | 86.7 | |
| Standard AugModel=Swin-T2026.06 | 86.7 | |
| DBAModel=ViT-B/162026.06 | 86.6 | |
| Standard AugModel=DenseNet-1212026.06 | 86.5 | |
| No AugModel=EfficientNet-B42026.06 | 86.5 | |
| GenMixModel=ResNet-502026.06 | 86.4 | |
| SaliencyMixModel=ViT-B/162026.06 | 86.3 | |
| GenMixModel=ViT-B/162026.06 | 86 | |
| MixupModel=ResNet-502026.06 | 85.9 | |
| No AugModel=Swin-T2026.06 | 85.9 | |
| No AugModel=DenseNet-1212026.06 | 85.8 | |
| MixupModel=ViT-B/162026.06 | 85.6 | |
| Standard AugModel=ResNet-502026.06 | 85.3 | |
| Standard AugModel=ViT-B/162026.06 | 85 | |
| No AugModel=ResNet-502026.06 | 84.6 | |
| No AugModel=ViT-B/162026.06 | 84.2 |