Image Classification on BIOSCAN-5M
96.81AccuracyBioAutoML-NAS
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| BioAutoML-NAS2025.10 | 96.81 | 97.46 | 96.81 | 97.05 | |
| BioAutoML-NAS2025.10 | 96.81 | 97.46 | 96.81 | 97.05 | |
| NAO2025.10 | 88.75 | 89.2 | 88.3 | 88.74 | |
| ENAS2025.10 | 86.5 | 87 | 86 | 86.5 | |
| SMAC3configuration=Bayesian Opt.2025.10 | 84.85 | 85.3 | 84.3 | 84.79 | |
| Optunaconfiguration=HPO for CNN2025.10 | 84.1 | 84.65 | 83.5 | 84.06 | |
| AutoKeras2025.10 | 83.2 | 83.9 | 82.5 | 83.19 | |
| AutoGluon2025.10 | 82.25 | 82.9 | 81.5 | 82.19 | |
| EfficientNet-B72025.10 | 79.23 | 79.4 | 78.8 | 79.08 | |
| TPOT2025.10 | 79.1 | 79.7 | 78.5 | 79.09 | |
| ConvNeXt-XL2025.10 | 78.55 | 78.7 | 78.2 | 78.4 | |
| Big Transfer (BiT)2025.10 | 78.11 | 78.3 | 77.7 | 77.96 | |
| Xception2025.10 | 77.43 | 77.6 | 77 | 77.27 | |
| DenseNet-2012025.10 | 76.68 | 76.9 | 76.2 | 76.53 | |
| DenseNet-1212025.10 | 70.28 | 70.5 | 69.8 | 70.14 | |
| MobileNetV22025.10 | 68.83 | 69 | 68.4 | 68.68 | |
| VGG162025.10 | 66.69 | 66.8 | 66.3 | 66.55 | |
| VGG192025.10 | 66.39 | 66.5 | 66 | 66.25 | |
| ResNet-182025.10 | 64.76 | 65.1 | 64.2 | 64.62 |