A Deep Bidirectional GRU Network Model for Biometric Electrocardiogram Classification Based on Recurrent Neural Networks

A Deep Bidirectional GRU Network Model for Biometric Electrocardiogram Classification Based on Recurrent Neural Networks

In this paper, we propose a deep Recurrent Neural Networks (RNNs) based on Gated Recurrent Unit (GRU) in a bidirectional manner (BGRU) for human identification from electrocardiogram (ECG) based biometrics, a classification task which aims to identify a subject from a given time-series sequential da...

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Bibliographic Details
Main Authors: Htet Myet Lynn, Sung Bum Pan, Pankoo Kim
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
1D-convolutional neural networks
bidriectional recurrent neural networks
biometrics classification
ECG signals
gated recurrent unit
user identification
Online Access:https://ieeexplore.ieee.org/document/8826253/

Internet

https://ieeexplore.ieee.org/document/8826253/

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