| Benchmark | Model | Rank | Results |
|---|---|---|---|
| fine-grained-image-classification-on-caltech | ResNet-101 (ideal number of groups) | – | Top-1 Error Rate: 22.247% |
| fine-grained-image-classification-on-oxford-2 | ResNet-101 (ideal number of groups) | – | Accuracy: 77.076 |
| image-classification-on-mnist | MLP (ideal number of groups) | – | Percentage error: 1.67 |
| object-detection-on-coco-2017 | Faster R-CNN (ideal number of groups) | – | AP: 40.7AP50: 61.2AP75: 44.6 |