Deep Learning Techniques Based Secured Biometric Authentication and Classification using ECG Signal-Reference-Cited by-同舟云学术

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Deep Learning Techniques Based Secured Biometric Authentication and Classification using ECG Signal

Published:2023-11-24 Issue: Volume:6 Page:1-5
ISSN:
Container-title:2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS)
language:
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Author:

Saravanan V¹,Parameshachari B.D²,Hussein Abbas Hameed Abdul³,Shilpa N⁴,Adnan Myasar Mundher⁵

Affiliation:

1. Saveetha Institute of Medical and Technical Sciences,Saveetha School of Engineering,Department of Nano Electronics Materials and Sensors,Chennai,India

2. Nitte Meenakshi Institute of Technology,Department of Electronics and Communication Engineering,Bengaluru,India

3. Ahl Al Bayt University,College of Pharmacy,Karbala,Iraq

4. SR University,School of Engineering,Department of ECE,Warangal,India

5. The Islamic university,Najaf,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420831/10420858/10421295.pdf?arnumber=10421295

Reference15 articles.

1. Biometric Authentication from Photic Stimulated EEG Records

2. A Privacy-Preserving Biometric Authentication System With Binary Classification in a Zero Knowledge Proof Protocol

3. Multimodal biometric authentication based on deep fusion of electrocardiogram (ECG) and finger vein

4. SaS-BCI: a new strategy to predict image memorability and use mental imagery as a brain-based biometric authentication

5. Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms

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