Deep convolutional neural networks for COVID-19 automatic diagnosis.
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| Title: | Deep convolutional neural networks for COVID-19 automatic diagnosis. |
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| Authors: | Emara HM; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., Shoaib MR; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., Elwekeil M; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., El-Shafai W; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.; Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh, Saudi Arabia., Taha TE; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., El-Fishawy AS; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., El-Rabaie EM; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., Alshebeili SA; Electrical Engineering Department, KACST-TIC in Radio Frequency and Photonics for the e-Society (RFTONICS), King Saud University, Riyadh, Saudi Arabia.; Department of Electrical Engineering, King Saud University, Riyadh, Saudi Arabia., Dessouky MI; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt., Abd El-Samie FE; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia. |
| Source: | Microscopy research and technique [Microsc Res Tech] 2021 Nov; Vol. 84 (11), pp. 2504-2516. Date of Electronic Publication: 2021 Jun 14. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Wiley-Liss Country of Publication: United States NLM ID: 9203012 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0029 (Electronic) Linking ISSN: 1059910X NLM ISO Abbreviation: Microsc Res Tech Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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