Sep 1, 2019 · This work introduced an ECG-based biometric recognition approach, called Deep-ECG. This approach is based on deep Convolutional Neural Networks ...
Deep learning methods, like Convolutional Neural Networks (CNNs), can automatically extract distinctive features, and have demonstrated their effectiveness for ...
Sep 1, 2019 · Deep-ECG performs identification and verification with remarkable accuracy. ... Deep-ECG is the first approach that uses deep CNNs for ECG ...
Mar 16, 2023 · Electrocardiogram (ECG) biometric provides an authentication to identify an individual on the basis of specific cardiac potential measured ...
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Convolutional Neural Networks for ECG biometric recognition
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The proposed model optimizes the features for classification by superimposing CNN onto the BiLSTM network layer, and achieves the effective mining and ...
Jan 23, 2023 · ECG-based biometric recognition on a large database using. 2D Convolutional neural networks was performed by Hong et al. [43]. Moreover, ECG.
Based on the MIT-BIT database of normal sinus rhythm, this paper proposes a hybrid deep neural network model for biometric recognition using convolutional ...
Feb 23, 2024 · Our goal is to examine and develop the best segmentation and deep learning model for identification system using arrhythmic ECG signals. Figure ...
1) A novel 2D representation of ECG: We propose a novel multi-scale continuous wavelet transform feature method to accurately obtain micro-texture and 2D rep-.
Jun 9, 2021 · This paper investigates how a short segment of an ECG signal can be effectively used for biometric recognition, using deep-learning techniques.