Image Classification on BloodMNIST v2 (test)
99.8AUCResNet-18
Evaluation results
| Method | Links | ||
|---|---|---|---|
| ResNet-18Input Resolution=282026.02 | 99.8 | 95.8 | |
| ResNet-18Input Resolution=2242026.02 | 99.8 | 96.3 | |
| AutoKeras2026.02 | 99.8 | 96.1 | |
| Google AutoML Vision2026.02 | 99.8 | 96.6 | |
| ResNet-50Input Resolution=282026.02 | 99.7 | 95.6 | |
| ResNet-50Input Resolution=2242026.02 | 99.7 | 95.6 | |
| auto-sklearn2026.02 | 98.4 | 87.8 | |
| G-LoG bi-filtration (MLP)Sigma (σ)=0.52026.02 | 97.9 | 84.4 | |
| G-LoG bi-filtration (MLP)Sigma (σ)=1.52026.02 | 97.8 | 84.6 | |
| G-LoG bi-filtration (MLP)Sigma (σ)=02026.02 | 97.7 | 84.7 | |
| G-LoG bi-filtration (MLP)Sigma (σ)=12026.02 | 97.7 | 84 | |
| Topo-Med (MLP)2026.02 | 97.3 | 79.8 |