2020
DOI: 10.5505/pajes.2019.32966
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ECG based biometric identification method using QRS images and convolutional neural network

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Cited by 4 publications
(4 citation statements)
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“…Due to the ever-increasing computational power, several CNN-based methods for ECG biometric identification have been recently proposed to increase identification performance and classification accuracy. In [31], Gurkan and Hanilci proposed an ECG-based biometric identification method using QRS images and two-dimensional CNN. These research lines will be pursued in our future work.…”
Section: Discussionmentioning
confidence: 99%
“…Due to the ever-increasing computational power, several CNN-based methods for ECG biometric identification have been recently proposed to increase identification performance and classification accuracy. In [31], Gurkan and Hanilci proposed an ECG-based biometric identification method using QRS images and two-dimensional CNN. These research lines will be pursued in our future work.…”
Section: Discussionmentioning
confidence: 99%
“…In the MIT-BIH database, the noise of the signals is removed by the filter in paper [38], while the proposed algorithm still achieves recognition accuracy of 100% without denoising process, which is more convenient for algorithm implementation. In contrast, the feature extraction method in [39,40] relies on the accuracy of traditional QRS positioning, so the detection rate is easy to affect the final recognition accuracy. The proposed two-level fusion feature algorithm realizes the complementary advantages of statistical feature and deep high-order feature and achieves a relatively high recognition accuracy of 99.77% on the mixed data set.…”
Section: Comparison Experiments Of the Related Researchesmentioning
confidence: 99%
“…Kiran et al extracted six optimal P-QRS-T segments based on their priority and positions, and employed the SVM (Support Vector Machine) algorithm for classification [10]. Gurkan et al extracted QRS complex and used convolutional neural networks for recognition [11].…”
Section: Introductionmentioning
confidence: 99%