A Comparative Study of Deep Learning Models for COVID-19 Diagnosis Based on X-Ray Images-Reference-Cited by-同舟云学术

A Comparative Study of Deep Learning Models for COVID-19 Diagnosis Based on X-Ray Images

Published:2022 Issue: Volume: Page:163-174
ISSN:2662-6829
Container-title:Advances in Sustainability Science and Technology
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Author:

Siddiqui Shah^ORCID,Hossain Elias^ORCID,Ferdous Rezowan^ORCID,Arifeen Murshedul^ORCID,Rahman Wahidur^ORCID,Masum Shamsul^ORCID,Hopgood Adrian^ORCID,Good Alice^ORCID,Gegov Alexander^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-9101-0_12

Reference30 articles.

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2. Althnian A, AlSaeed D, Al-Baity H, Samha A, Dris AB, Alzakari N, Abou Elwafa A, Kurdi H (2021) Impact of dataset size on classification performance: an empirical evaluation in the medical domain. Appl Sci 11(2):796

3. Bar Y, Diamant I, Wolf L, Greenspan H (2015) Deep learning with non-medical training used for chest pathology identification. In: Medical imaging 2015: computer-aided diagnosis. vol 9414, p 94140V. International Society for Optics and Photonics

4. Barbedo JGA (2018) Impact of dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification. Comput Electron Agric 153:46–53

5. BBC: Coronavirus: cases of new variant appear worldwide (2020). https://www.bbc.com/news/world-europe-55452262. Accessed 09 May 2021

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