ECG arrhythmia classification using modified visual geometry group network (mVGGNet)

Author:

Jangra Manisha1,Dhull Sanjeev Kr.1,Singh Krishna Kant2

Affiliation:

1. Department of ECE, Guru Jambheshwar University of Science & Technology, Hisar, Haryana, India

2. Department of Electronics and Communication Engineering, KIET Group of Institutions, Ghaziabad, India

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference40 articles.

1. ECG arrhythmia classification using a 2-D convolutional neural network;Jun;Computer Vision and Pattern Recognition,2018

2. Recent trends in arrhythmia beat detection: A review;Jangra;Proceedings of the International Conference on Communication and Computing Systems,2017

3. Using feed forward neural network for electrocardiogram signal analysis in chaotic domain;Nejad;Journal of Intelligent Fuzzy System,2014

4. CPS-based Fully Automatic Cardiac Left Ventricle and Left Atrium Segmentation in 3D MRI;Ahmad;Journal of Intelligent Fuzzy System,2019

5. Automatic segmentation of coronary tree in CT angiography images;Gao;International Journal of Adaptive Control and Signal Processing,2017

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