Convolutional neural network optimized by differential evolution for electrocardiogram classification-Reference-Cited by-同舟云学术

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Convolutional neural network optimized by differential evolution for electrocardiogram classification

Published:2023-04-26 Issue:29 Volume:82 Page:45811-45837
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Chen Shan Wei,Wang Shir Li^ORCID,Qi XiuZhi,Ng Theam Foo,Ibrahim Haidi

Funder

Ministry of Education Malaysia

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-15407-9.pdf

Reference31 articles.

1. Acharya UR et al (2017) A deep convolutional neural network model to classify heartbeats. Comput Biol Med 89:389–396. https://doi.org/10.1016/j.compbiomed.2017.08.022

2. Aghamaleki JA, AshkaniChenarlogh V (2019) Multi-stream CNN for facial expression recognition in limited training data. Multimed Tools Appl 78(16):22861–22882. https://doi.org/10.1007/s11042-019-7530-7

3. Bhagyalakshmi V, Pujeri RV, Devanagavi GD (2021) GB-SVNN: Genetic BAT assisted support vector neural network for arrhythmia classification using ECG signals. J King Saud Univ Inf Sci 33(1):54–67. https://doi.org/10.1016/j.jksuci.2018.02.005

4. Chandra BS, Sastry CS, Jana S (2019) Robust Heartbeat Detection from Multimodal Data via CNN-Based Generalizable Information Fusion. IEEE Trans Biomed Eng 66(3):710–717. https://doi.org/10.1109/TBME.2018.2854899

5. Degirmenci M, Ozdemir MA, Izci E, Akan A (2022) Arrhythmic heartbeat classification using 2d convolutional neural networks. Irbm 43(5):422–433

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