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Journals
Journal of Artificial Intelligence and Soft Computing Research
Volume 13 (2023): Issue 3 (June 2023)
Open Access
A Novel Method for Automatic Detection of Arrhythmias Using the Unsupervised Convolutional Neural Network
Junming Zhang
Junming Zhang
College of Information Engineering, Huanghuai University
Henan, China
Henan Key Laboratory of Smart Lighting
Henan, China
Henan Joint International Research Laboratory of Behavior Optimization Control for Smart Robots
Henan, China
Zhumadian Artificial Intelligence & Medical Engineering Technical Research Centre
Henan, China
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Zhang, Junming
,
Ruxian Yao
Ruxian Yao
College of Information Engineering, Huanghuai University
Henan, China
Henan Key Laboratory of Smart Lighting
Henan, China
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Yao, Ruxian
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Jinfeng Gao
Jinfeng Gao
College of Information Engineering, Huanghuai University
Henan, China
Henan Key Laboratory of Smart Lighting
Henan, China
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Gao, Jinfeng
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Gangqiang Li
Gangqiang Li
College of Information Engineering, Huanghuai University
Henan, China
Henan Key Laboratory of Smart Lighting
Henan, China
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Li, Gangqiang
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Haitao Wu
Haitao Wu
College of Information Engineering, Huanghuai University
Henan, China
Henan Key Laboratory of Smart Lighting
Henan, China
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Wu, Haitao
Jun 23, 2023
Journal of Artificial Intelligence and Soft Computing Research
Volume 13 (2023): Issue 3 (June 2023)
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Published Online:
Jun 23, 2023
Page range:
181 - 196
Received:
Jan 28, 2023
Accepted:
May 17, 2023
DOI:
https://doi.org/10.2478/jaiscr-2023-0014
Keywords
convolutional neural network
,
arrhythmia detection
,
unsupervised learning
,
ECG classification
© 2023 Junming Zhang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.