Skin Lesion Classification on ISIC 2019
93.95AccuracyJi et al.
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| Ji et al.2025.12 | 93.95 | — | — | — | — | |
| soft voting ensemble of CNNsBackbone=MobileNetV22025.12 | 93.92 | — | — | — | — | |
| Zhi et al.2025.12 | 89.04 | — | — | — | — | |
| Swin Transformer + BatchFormer + Focal Loss + ReduceLROnPlateauModel Category=Transformer2026.01 | 87.71 | — | — | — | — | |
| ECL2023.07 | 86.11 | 76.57 | 83.22 | 79.46 | 96.78 | |
| Moazen & Jamzad2025.10 | 84.86 | 84.85 | — | 46.82 | — | |
| Setiawan2025.10 | 84.76 | — | — | — | — | |
| TSC2023.07 | 84.75 | 71.89 | 79.81 | 75.13 | 95.84 | |
| Hybrid-SC2023.07 | 84.69 | 70.9 | 76.87 | 73.27 | 96.67 | |
| SCL2023.07 | 84.6 | 70.9 | 81.66 | 75.07 | 96.21 | |
| MWNL2023.07 | 84.1 | 74.83 | 75.81 | 75.08 | 96.61 | |
| BCL2023.07 | 83.47 | 73.52 | 74.17 | 73.5 | 95.95 | |
| BBN2023.07 | 83.43 | 71.78 | 78.37 | 74.42 | 95.1 | |
| Gun et al.2025.12 | 83 | — | — | — | — | |
| CE2023.07 | 82.41 | 67.02 | 77.32 | 70.9 | 95.37 | |
| LDAM-DRW2023.07 | 82.29 | 68.08 | 74.61 | 70.84 | 95.65 | |
| Focal Loss2023.07 | 82.05 | 64.55 | 75.93 | 68.84 | 94.82 | |
| Logit Adjust2023.07 | 81.93 | 68.94 | 69.12 | 68.64 | 95.17 | |
| EfficientNetModel Category=CNN2026.01 | 80.94 | — | — | — | — | |
| DenseNet121 + Fourier TransformerModel Category=CNN2026.01 | 80.16 | — | — | — | — | |
| ViTModel Category=Transformer2026.01 | 80.16 | — | — | — | — | |
| DenseNet121-CEModel Category=CNN2026.01 | 76.47 | — | — | — | — | |
| Ensemble (Weighted)Model Category=CNN2026.01 | 73.18 | — | — | — | — | |
| ResNet50 + SimAMModel Category=CNN2026.01 | 69.18 | — | — | — | — | |
| Ensemble (Concatenated)Model Category=CNN2026.01 | 68.89 | — | — | — | — | |
| DenseNet121-MWNLModel Category=CNN2026.01 | 61.37 | — | — | — | — | |
| U-NetModel Category=CNN2026.01 | 60.52 | — | — | — | — | |
| Gessert et al.2025.10 | — | 59.4 | — | — | 92.8 |