| Hyperparticle/one-pixel-attack-keras |
1,078 |
|
0 |
0 |
over 5 years ago |
0 |
|
4 |
mit |
Jupyter Notebook |
| Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet |
| TsingZ0/PFLlib |
935 |
|
0 |
0 |
about 2 years ago |
0 |
|
7 |
gpl-2.0 |
Python |
| Personalized federated learning simulation platform with non-IID and unbalanced dataset |
| facebookresearch/ImageNet-Adversarial-Training |
510 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
other |
Python |
| ImageNet classifier with state-of-the-art adversarial robustness |
| huanzhang12/ZOO-Attack |
123 |
|
0 |
0 |
over 4 years ago |
0 |
|
4 |
other |
Python |
| ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks |
| labsix/limited-blackbox-attacks |
98 |
|
0 |
0 |
about 6 years ago |
0 |
|
6 |
|
Python |
| Code for "Black-box Adversarial Attacks with Limited Queries and Information" (http://arxiv.org/abs/1804.08598) |
| huanzhang12/Adversarial_Survey |
86 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
|
Python |
| Robustness vs Accuracy Survey on ImageNet |
| ddkang/advex-uar |
77 |
|
0 |
1 |
almost 4 years ago |
6 |
April 26, 2022 |
5 |
apache-2.0 |
Python |
| Code for "Testing Robustness Against Unforeseen Adversaries" |
| trx14/TrojanNet |
75 |
|
0 |
0 |
over 2 years ago |
0 |
|
4 |
mit |
Python |
| poloclub/jpeg-defense |
65 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
mit |
Python |
| SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression |
| xuanqing94/RobGAN |
51 |
|
0 |
0 |
almost 7 years ago |
0 |
|
2 |
mit |
Python |
| Rob-GAN: Generator, Discriminator and Adversarial Attacker |
