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Imbalanced Ectopic Beat Classification Using a Low-Memory-Usage CNN LMUEBCNet and Correlation-Based ECG Signal Oversampling

<i>Objective:</i> This study presents a low-memory-usage ectopic beat classification convolutional neural network (CNN) (LMUEBCNet) and a correlation-based oversampling (Corr-OS) method for ectopic beat data augmentation. <i>Methods</i>: A LMUEBCNet classifier consists of four VGG-based convolution...

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Principais autores: You-Liang Xie, Che-Wei Lin
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2023-04-01
Serier:Mathematics
Fag:
ectopic beat classification
MIT-BIH
AAMI
low memory usage
convolutional neural network (CNN)
data augmentation
Online adgang:https://www.mdpi.com/2227-7390/11/8/1833
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