COVID-19 disease diagnosis with light-weight CNN using modified MFCC and enhanced GFCC from human respiratory sounds

Author:

Kranthi Kumar LellaORCID,Alphonse P.J.A.ORCID

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy,General Materials Science

Reference41 articles.

1. World Health Organization. Coronavirus disease (COVID-19) ( 2019), https://www.who.int/

2. Y. Wang, M. Hu, Q. Li et al., Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner (2020). arXiv:2002.05534 [cs.LG]

3. Z. Jiang, M. Hu, F. Lei et al., Combining visible light and infrared imaging for efficient detection of respiratory infections such as COVID-19 on portable device (2020). arXiv:2004.06912 [cs.CV]

4. A. Imran, I. Posokhova, H.N. Qureshi et al., AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app. Inform. Med. Unlocked 20, 100378 (2020)

5. J. Shuja, E. Alanazi, W. Alasmary et al., COVID-19 open source data sets: a comprehensive survey. Appl. Intell. 21, 1–30 (2020)

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