Multilevel Classification and Detection of Cardiac Arrhythmias With High-Resolution Superlet Transform and Deep Convolution Neural Network-Reference-Cited by-同舟云学术

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Multilevel Classification and Detection of Cardiac Arrhythmias With High-Resolution Superlet Transform and Deep Convolution Neural Network

Published:2022 Issue: Volume:71 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Tripathi Prashant Mani¹^ORCID,Kumar Ashish²^ORCID,Kumar Manjeet³^ORCID,Komaragiri Rama¹^ORCID

Affiliation:

1. Department of Electronics and Communication Engineering, Bennett University, Greater Noida, India

2. School of Electronics Engineering, Vellore Institute of Technology, Chennai, India

3. Department of Electronics and Communication Engineering, Delhi Technological University, New Delhi, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09807318.pdf?arnumber=9807318

Reference63 articles.

1. Classification of 12-lead ECG signals with bi-directional LSTM network;mostayed;arXiv 1811 02090,2018

2. ECG Arrhythmia Classification Using Transfer Learning from 2- Dimensional Deep CNN Features

3. A Multitier Deep Learning Model for Arrhythmia Detection

4. Towards End-to-End ECG Classification With Raw Signal Extraction and Deep Neural Networks

5. Intelligent and Efficient Detection of Life-Threatening Ventricular Arrhythmias in Short Segments of Surface ECG Signals

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