Corpus ID: 236033993

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks

@article{Hossain2021ECGAdvGANDE,
  title={ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks},
  author={Khondker Fariha Hossain and Sharif Amit Kamran and A. Tavakkoli and Lei Pan and Daniel Ma and Sutharshan Rajasegarar and Chandan Karmaker},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.07677}
}
Electrocardiogram (ECG) acquisition requires an automated system and analysis pipeline for understanding specific rhythm irregularities. Deep neural networks have become a popular technique for tracing ECG signals, outperforming human experts. Despite this, convolutional neural networks are susceptible to adversarial examples that can misclassify ECG signals and decrease the model’s precision. Moreover, they do not generalize well on the out-of-distribution dataset. The GAN architecture has… Expand

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