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What is (Jan2020) ECG-Based Human Identification Using Spectral Correlation about?

This paper presents a novel ECG-based human identification approach utilizing spectral correlation and deep learning techniques. The method segments ECG signals, enhances their information content, and employs convolutional neural networks to improve identification accuracy, achieving rates of 95.6% with low false acceptance and rejection rates. The study demonstrates the advantages of ECG as a biometric modality, including its difficulty to counterfeit and its unique physiological characteristics.

Author

priyankag.ec.19

Language

EN