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
Jezik:	Inglês
Izdano:	MDPI AG 2023-04-01
Serija:	Mathematics
Teme:	ectopic beat classification MIT-BIH AAMI low memory usage convolutional neural network (CNN) data augmentation
Online dostop:	https://www.mdpi.com/2227-7390/11/8/1833
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