Monkeypox Detection on Monkeypox Dataset
0.9651AccuracyRSwinV2
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| RSwinV22026.01 | 0.9651 | 0.9621 | 0.9604 | 0.9613 | |
| SwinV22026.01 | 0.9603 | 0.9502 | 0.9582 | 0.9542 | |
| MobileNet-V2Model Category=Existing CNN's2026.01 | 0.954 | 0.942 | — | 0.94 | |
| Swin T2026.01 | 0.9531 | 0.9499 | 0.9493 | 0.9496 | |
| DenseNet201Model Category=Existing CNN's2026.01 | 0.9518 | 0.8982 | — | 0.8961 | |
| Mobile ViT2026.01 | 0.9513 | 0.9419 | 0.9434 | 0.9427 | |
| ResNet 182026.01 | 0.9477 | 0.9406 | 0.9428 | 0.9417 | |
| ViT'sModel Category=Existing ViT's, Reference=[24]2026.01 | 0.9469 | 0.95 | — | 0.95 | |
| VGG 162026.01 | 0.9441 | 0.9407 | 0.9317 | 0.9362 | |
| Tiny ViT2026.01 | 0.9441 | 0.9407 | 0.9317 | 0.9362 | |
| Google-Net and Metaheuristic OptimizationModel Category=Hybrid Techniques2026.01 | 0.9435 | 0.95 | — | 0.92 | |
| DarkNet 532026.01 | 0.9321 | 0.929 | 0.9161 | 0.9225 | |
| Local ViT2026.01 | 0.9321 | 0.929 | 0.9161 | 0.9225 | |
| ViT'sModel Category=Existing ViT's, Reference=[22]2026.01 | 0.93 | 0.91 | — | 0.92 | |
| ViT'sModel Category=Existing ViT's, Reference=[25]2026.01 | 0.93 | 0.93 | — | 0.93 | |
| Cross ViT2026.01 | 0.9296 | 0.9137 | 0.9242 | 0.9189 | |
| Mobile Net V42026.01 | 0.9218 | 0.9117 | 0.9167 | 0.9142 | |
| MobileNetv2Model Category=Existing CNN's2026.01 | 0.9111 | 0.9 | — | 0.9 | |
| VGG-16 (naïve Bayes)Model Category=Hybrid Techniques2026.01 | 0.9111 | — | — | — | |
| RestNet50 with TLModel Category=Hybrid Techniques2026.01 | 0.91 | 0.9 | — | 0.9 | |
| 13 DL models and Ensemble methodModel Category=Hybrid Techniques2026.01 | 0.8713 | 0.8547 | — | 0.854 | |
| DarkNet-53Model Category=Existing CNN's2026.01 | 0.8578 | 0.8246 | — | 0.842 | |
| Xception CBAM DenseModel Category=Hybrid Techniques2026.01 | 0.839 | 0.891 | — | 0.901 | |
| ResNet50Model Category=Existing CNN's2026.01 | 0.8296 | 0.83 | — | 0.84 | |
| Ensemble ViT’s with Densenet-201Model Category=Hybrid Techniques2026.01 | 0.8191 | 0.7414 | — | 0.7816 | |
| ShuffleNetV2Model Category=Existing CNN's2026.01 | 0.79 | 0.58 | — | 0.67 | |
| ViTB-18Model Category=Existing ViT's2026.01 | 0.7155 | 0.7926 | — | 0.6111 |