A comparative analysis of deep neural network architectures for the dynamic diagnosis of COVID‐19 based on acoustic cough features-Reference-Cited by-同舟云学术

A comparative analysis of deep neural network architectures for the dynamic diagnosis of COVID‐19 based on acoustic cough features

Published:2022-05-21 Issue:5 Volume:32 Page:1433-1446
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Tech

Author:

Sunitha Gurram¹,Arunachalam Rajesh²,Abd‐Elnaby Mohammed³,Eid Mahmoud M. A.⁴,Rashed Ahmed Nabih Zaki⁵^ORCID

Affiliation:

1. Department of Computer Science Engineering Sree Vidyanikethan Engineering College Tirupati Andhra Pradesh India

2. Department of Electronics and Communication Engineering CVR College of Engineering (Autonomous) Hyderabad Telangana 501510 India

3. Department of Computer Engineering, College of Computers and Information Technology Taif University P.O. Box 11099 Taif 21944 Saudi Arabia

4. Department of Electrical Engineering, College of Engineering Taif University P.O. Box 11099 Taif 21944 Saudi Arabia

5. Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering, Menoufia University Menouf Egypt

Funder

Taif University

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22749

Reference51 articles.

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3. Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID‐19 disease;Struyf T;Cochrane Database Syst Rev,2020

4. Epidemiological and Clinical Characteristics of COVID-19 in Adolescents and Young Adults

5. RameshG.Researcher at Bosch Centre for Data Science and AI at IIT Madras and Dr. SundeepTeki a leader in AI and Neuroscience.https://www.kdnuggets.com/2020/12/covid-cough-ai-detecting-sounds.html

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