AE-GAN: adversarial eliminating with GAN

@article{Shen2017AEGANAE,
  title={AE-GAN: adversarial eliminating with GAN},
  author={Shiwei Shen and Guoqing Jin and Ke Gao and Yongdong Zhang},
  journal={CoRR},
  year={2017},
  volume={abs/1707.05474}
}
Although neural networks could achieve state-of-the-art performance while recongnizing images, they often suffer a tremendous defeat from adversarial examples–inputs generated by utilizing imperceptible but intentional perturbation to clean samples from the datasets. How to defense against adversarial examples is an important problem which is well worth researching. So far, very few methods have provided a significant defense to adversarial examples. In this paper, a novel idea is proposed and… CONTINUE READING