| image-classification-on-imagenet | ReXNet-R_3.0 | #331 | Top 1 Accuracy: 84.5%Number of params: 34.8M |
| image-classification-on-imagenet | ReXNet-R_2.0 | #481 | Top 1 Accuracy: 83.2%Number of params: 16.5M |
| image-classification-on-imagenet | ReXNet_3.0 | #524 | Top 1 Accuracy: 82.8%Number of params: 34.7MGFLOPs: 3.4 |
| image-classification-on-imagenet | ReXNet_2.0 | #655 | Top 1 Accuracy: 81.6%Number of params: 19MGFLOPs: 1.5 |
| image-classification-on-imagenet | ReXNet_1.5 | #747 | Top 1 Accuracy: 80.3%Number of params: 9.7MGFLOPs: 0.86 |
| image-classification-on-imagenet | ReXNet_1.3 | #788 | Top 1 Accuracy: 79.5%Number of params: 7.6MGFLOPs: 0.66 |
| image-classification-on-imagenet | ReXNet_1.0 | #895 | Top 1 Accuracy: 77.9%Number of params: 4.8MGFLOPs: 0.40 |
| image-classification-on-imagenet | ReXNet_0.9 | #924 | Top 1 Accuracy: 77.2%Number of params: 4.1MGFLOPs: 0.35 |
| image-classification-on-imagenet | ReXNet_0.6 | #1017 | Top 1 Accuracy: 74.6%Number of params: 2.7M |