ResNet‐Attention model for human authentication using ECG signals-Reference-Cited by-同舟云学术

ResNet‐Attention model for human authentication using ECG signals

Published:2020-03-10 Issue:6 Volume:38 Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Hammad Mohamed¹²,Pławiak Paweł³⁴^ORCID,Wang Kuanquan¹,Acharya Udyavara Rajendra⁵⁶⁷

Affiliation:

1. School of Computer Science and Technology Harbin Institute of Technology Harbin China

2. Faculty of Computers and Information Menoufia University Menoufia Egypt

3. Department of Information and Communications Technology, Faculty of Computer Science and Telecommunications Cracow University of Technology Krakow Poland

4. Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland

5. Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore Singapore

6. Department of Biomedical Engineering, School of Science and Technology Singapore School of Social Sciences Singapore Singapore

7. Department of Bioinformatics and Medical Engineering Asia University Taichung Taiwan

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12547

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5. Bin Safie S. I. Nurfazira H. Azavitra Z. Soraghan J. &Petropoulakis L. (2014). Pulse active transform (PAT): A non‐invertible transformation with application to ECG biometric authentication. In: Region 10 Symposium IEEE.

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