Stacked Dark COVID-Net: A Multi-class Multi-label Classification Approach for Diagnosing COVID-19 Using Chest X-Ray Images-Reference-Cited by-同舟云学术

Stacked Dark COVID-Net: A Multi-class Multi-label Classification Approach for Diagnosing COVID-19 Using Chest X-Ray Images

Published:2022 Issue: Volume: Page:61-75
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Anila Glory H.^ORCID,Meghana S.,Kesav Kumar J. S.,Shankar Sriram V. S.^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-07005-1_7

Reference32 articles.

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3. Ozturk, T., Talo, M., Yildirim, E.A., Baloglu, U.B., Yildirim, O., Rajendra Acharya, U.: Automated detection of COVID-19 cases using deep neural networks with X-ray images. Comput. Biol. Med. 121, 103792 (2020). https://doi.org/10.1016/j.compbiomed.2020.103792

4. Symptoms of Coronavirus. https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html

5. Lau, S.K.P., Che, X., Woo, P.C.Y., Wong, B.H.L., Chan, K., Peiris, J.S.M.: SARS Coronavirus detection methods. Emerg. Infect. Dis. 11, 7–10 (2005)

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