Monkeypox Detection on Monkeypox Dataset benchmark leaderboard · SOTA2 Research

Monkeypox Detection on Monkeypox Dataset

0.9651AccuracyRSwinV2

Evaluation Results

Method
RSwinV22026.01	0.9651	0.9621	0.9604	0.9613
SwinV22026.01	0.9603	0.9502	0.9582	0.9542
MobileNet-V22026.01	0.954	0.942	—	0.94
Swin T2026.01	0.9531	0.9499	0.9493	0.9496
DenseNet2012026.01	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's2026.01	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 Optimization2026.01	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's2026.01	0.93	0.91	—	0.92
ViT's2026.01	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
MobileNetv22026.01	0.9111	0.9	—	0.9
VGG-16 (naïve Bayes)2026.01	0.9111	—	—	—
RestNet50 with TL2026.01	0.91	0.9	—	0.9
13 DL models and Ensemble method2026.01	0.8713	0.8547	—	0.854
DarkNet-532026.01	0.8578	0.8246	—	0.842
Xception CBAM Dense2026.01	0.839	0.891	—	0.901
ResNet502026.01	0.8296	0.83	—	0.84
Ensemble ViT’s with Densenet-2012026.01	0.8191	0.7414	—	0.7816
ShuffleNetV22026.01	0.79	0.58	—	0.67
ViTB-182026.01	0.7155	0.7926	—	0.6111