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Enhancing deep learning techniques for the diagnosis of the novel coronavirus (COVID-19) using X-ray images

  • Published:2023-03-08 Issue:1 Volume:10 Page:
  • ISSN:2331-1916
  • Container-title:Cogent Engineering
  • language:en
  • Short-container-title:Cogent Engineering

Author:

Alghamdi Maha Mesfer Meshref1ORCID,Dahab Mohammed Yehia Hassan2,Alazwary Naael Homoud Abdulrahim3ORCID

Affiliation:

1. Computer Science & Engineering Department, King Saud University, Riyadh, Saudi Arabia

2. Department of Computing Science, King Abdulaziz University, Jeddah, Saudi Arabia

3. Department of Internal Medicine, Security Forces Hospital, KSA, Saudi Arabia

Funder

Ministry of Education and King Abdulaziz University

Publisher

Informa UK Limited

Subject

General Engineering,General Chemical Engineering,General Computer Science

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Local Binary Pattern and RVFL for Covid-19 Diagnosis;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024

2. Classification of Pneumonia Disease Through Deep Learning Procedures and Fine-tuning on ResNet50V2 CNN Model Utilizing Chest Xray Images;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01

3. $$\mathrm SRC_{2}$$: a novel deep learning based technique for identifying COVID-19 using images of chest x-ray;Multimedia Tools and Applications;2023-10-10

4. Exploring the Role of Python in Self-Supervised Contrastive Learning for Generating Medical Imaging Reports;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2023-06-30
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