Noise-Robust Sleep Staging via Adversarial Training With an Auxiliary Model

Author:

Yoo Chaehwa1ORCID,Liu Xiaofeng2ORCID,Xing Fangxu2ORCID,Fakhri Georges El2ORCID,Woo Jonghye2ORCID,Kang Je-Won3ORCID

Affiliation:

1. Department of Electronic and Electrical Engineering and Graduate Program in Smart Factory, Ewha W. University, South Korea

2. Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, USA

3. Department of Electronic and Electrical Engineering and Graduate Program in Smart Factory, Ewha W. University, Seoul, South Korea

Funder

Convergent Technology RnD Program for Human Augmentation

National Research Foundation of Korea

Ministry of Science and ICT, South Korea

NRF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Reference48 articles.

1. A Wavelet-Chaos Methodology for Analysis of EEGs and EEG Subbands to Detect Seizure and Epilepsy

2. Robustness may be at odds with accuracy;tsipras;Proc Int Conf Learn Representations,0

3. One Man’s Trash Is Another Man’s Treasure: Resisting Adversarial Examples by Adversarial Examples

4. Benchmarking neural network robustness to common corruptions and perturbations;hendrycks;Proc Int Conf Learn Representations,0

5. A novel end-to-end 1D-ResCNN model to remove artifact from EEG signals

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