| zhunzhong07/Random-Erasing |
697 |
|
0 |
0 |
over 2 years ago |
0 |
|
11 |
apache-2.0 |
Python |
| Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST |
| datawhalechina/dive-into-cv-pytorch |
504 |
|
0 |
0 |
almost 4 years ago |
0 |
|
7 |
gpl-3.0 |
Python |
| 动手学CV-Pytorch版 |
| shinseung428/CapsNet_Tensorflow |
70 |
|
0 |
0 |
about 8 years ago |
0 |
|
3 |
mit |
Python |
| cxy1997/MNIST-baselines |
45 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
mit |
Python |
| Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project |
| carlini/breaking_defensive_distillation |
20 |
|
0 |
0 |
almost 9 years ago |
0 |
|
0 |
gpl-3.0 |
Python |
| fomorians/counting-mnist |
8 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
apache-2.0 |
Jupyter Notebook |
| A simple synthetic dataset and baseline model for visual counting. |
| mkmenta/domain_adapt_segm |
7 |
|
0 |
0 |
about 6 years ago |
0 |
|
0 |
mit |
Python |
| Implementation of my Master Thesis "Learning to adapt class-specific features across domains for semantic segmentation". |
| zzzxxxttt/pytorch_simple_classification_baselines |
7 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
|
Python |
| Simple pytorch classification baselines for MNIST, CIFAR and ImageNet |
