Binary Classification on ISIC Clean 7
62AccuracyFT model
Evaluation results
| Method | Links | |
|---|---|---|
| FT modeln (number of cleansed samples)=10, Backbone=EfficientNet-B42026.03 | 62 | |
| Benign modelBackbone=EfficientNet-B42026.03 | 61.5 | |
| Dyn. rectifyingn (number of cleansed samples)=10, Backbone=EfficientNet-B42026.03 | 61 | |
| Stat. rectifyingn (number of cleansed samples)=10, Backbone=EfficientNet-B42026.03 | 60 | |
| A-ClArCn (number of cleansed samples)=20, Backbone=EfficientNet-B42026.03 | 54.5 | |
| FT modeln (number of cleansed samples)=20, Backbone=EfficientNet-B42026.03 | 53 |