The Effect of Data Augmentation on Classification of Atrial Fibrillation in Short Single-Lead ECG Signals Using Deep Neural Networks

Nejati Hatamian F, Ravikumar N, Vesal S, Kemeth FP, Struck M, Maier A (2020)

Publication Language: English

Publication Type: Conference contribution

Publication year: 2020

Publisher: IEEE

Event location: Barcelona, Spain ES

URI: https://ieeexplore.ieee.org/document/9053800

DOI: 10.1109/ICASSP40776.2020.9053800

Authors with CRIS profile

Faezeh Nejati Hatamian Lehrstuhl für Informatik 5 (Mustererkennung) Sulaiman Vesal Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

Involved external institutions

University of Leeds GB United Kingdom (GB) Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE) Johns Hopkins University (JHU) US United States (USA) (US)

How to cite

APA:

Nejati Hatamian, F., Ravikumar, N., Vesal, S., Kemeth, F.P., Struck, M., & Maier, A. (2020). The Effect of Data Augmentation on Classification of Atrial Fibrillation in Short Single-Lead ECG Signals Using Deep Neural Networks. In Proceedings of the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020). Barcelona, Spain, ES: IEEE.

MLA:

Nejati Hatamian, Faezeh, et al. "The Effect of Data Augmentation on Classification of Atrial Fibrillation in Short Single-Lead ECG Signals Using Deep Neural Networks." Proceedings of the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona, Spain IEEE, 2020.

BibTeX: Download