ARGAN: Adversarially Robust Generative Adversarial Networks for Deep Neural Networks Against Adversarial Examples

Seokhwan Choi, Jin-Myeong Shin, Peng Liu 0005, Yoon Ho Choi. ARGAN: Adversarially Robust Generative Adversarial Networks for Deep Neural Networks Against Adversarial Examples. IEEE Access, 10:33602-33615, 2022. [doi]

@article{ChoiSLC22,
  title = {ARGAN: Adversarially Robust Generative Adversarial Networks for Deep Neural Networks Against Adversarial Examples},
  author = {Seokhwan Choi and Jin-Myeong Shin and Peng Liu 0005 and Yoon Ho Choi},
  year = {2022},
  doi = {10.1109/ACCESS.2022.3160283},
  url = {https://doi.org/10.1109/ACCESS.2022.3160283},
  researchr = {https://researchr.org/publication/ChoiSLC22},
  cites = {0},
  citedby = {0},
  journal = {IEEE Access},
  volume = {10},
  pages = {33602-33615},
}