Dense Convolutional Networks With Focal Loss and Image Generation for Electrocardiogram Classification

Dense Convolutional Networks With Focal Loss and Image Generation for Electrocardiogram Classification

In this paper, we propose a novel end-to-end learnable architecture based on Dense Convolutional Networks (DCN) for the classification of electrocardiogram (ECG) signals. This architecture is based on two main modules: the first is a generative module and the second is a discriminative one. The task...

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Bibliographic Details
Main Authors: Mohamad Mahmoud Al Rahhal, Yakoub Bazi, Haidar Almubarak, Naif Alajlan, Mansour Al Zuair
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Generative
discriminative
ECG
classification
arrhythmia
Online Access:https://ieeexplore.ieee.org/document/8933368/

Internet

https://ieeexplore.ieee.org/document/8933368/

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