COVID-19 Diagnosis from Cough Acoustics using ConvNets and Data Augmentation-Reference-Cited by-同舟云学术

COVID-19 Diagnosis from Cough Acoustics using ConvNets and Data Augmentation

Published:2021-12-16 Issue: Volume: Page:
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Container-title:2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT)
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Author:

Mahanta Saranga Kingkor¹,Kaushik Darsh²,Van Truong Hoang³,Jain Shubham⁴,Guha Koushik¹

Affiliation:

1. National Institute of Technology,Electronics and Communication Engineering Department,Silchar,India 788010

2. National Institute of Technology,Computer Science and Engineering Department,Silchar,India 788010

3. University of Science of HCMC,Mathematics in Computer Science,Ho Chi Minh City,Vietnam 700000

4. Independent

Publisher

IEEE

Link

Reference29 articles.

2. Virufy: global applicability of crowdsourced and clinical datasets for ai detection of covid-19 from cough;chaudhari,2021

3. Virufy: a multi-branch deep learning network for automated detection of covid-19;fakhry,2021

5. Speech recognition using mfcc;ittichaichareon;International Conference on Computer Graphics Simulation and Modeling,2012

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3. Data Augmentation using Reverb and Noise in Deep Learning Implementation of Cough Classification;2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA);2023-06-14