A Comprehensive Review on COVID-19 Cough Audio Classification through Deep Learning-Reference-Cited by-同舟云学术

A Comprehensive Review on COVID-19 Cough Audio Classification through Deep Learning

Published:2023-11-10 Issue: Volume: Page:289-294
ISSN:2456-3307
Container-title:International Journal of Scientific Research in Computer Science, Engineering and Information Technology
language:en
Short-container-title:IJSRCSEIT

Author:

Gupta Praveen¹,Degadwala Sheshang²

Affiliation:

1. Research Scholar, Dept. of Computer Engineering, Sigma Institute of Engineering, Gujarat, India

2. Associate Professor & Head of Department, Dept. of Computer Engineering, Sigma University, Gujarat, India

Abstract

This review paper provides a comprehensive analysis of the advancements in COVID-19 cough audio classification through deep learning techniques. With the ongoing global pandemic, there is a growing need for non-intrusive and rapid diagnostic tools, and the utilization of audio-based methods for COVID-19 detection has gained considerable attention. The paper systematically reviews and compares various deep learning models, methodologies, and datasets employed for COVID-19 cough audio classification. The effectiveness, challenges, and future directions of these approaches are discussed, shedding light on the potential of audio-based diagnostics in the context of the current public health crisis.

Publisher

Technoscience Academy

Subject

General Earth and Planetary Sciences,General Environmental Science

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