Advanced Meta-Heuristics, Convolutional Neural Networks, and Feature Selectors for Efficient COVID-19 X-Ray Chest Image Classification-Reference-Cited by-同舟云学术

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Advanced Meta-Heuristics, Convolutional Neural Networks, and Feature Selectors for Efficient COVID-19 X-Ray Chest Image Classification

Published:2021 Issue: Volume:9 Page:36019-36037
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

El-Kenawy El-Sayed M.^ORCID,Mirjalili Seyedali^ORCID,Ibrahim Abdelhameed^ORCID,Alrahmawy Mohammed^ORCID,El-Said M.,Zaki Rokaia M.^ORCID,Eid Marwa Metwally^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09360538.pdf?arnumber=9360538

Cited by 105 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. Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection;Computers in Biology and Medicine;2024-11

2. Explainable SE-MobileNet for Pneumonia detection integrated with robustness assessment using adversarial examples;Smart Health;2024-09

3. Particle guided metaheuristic algorithm for global optimization and feature selection problems;Expert Systems with Applications;2024-08

4. A novel collocation method with a coronavirus optimization algorithm for the optimal control of COVID-19: A case study of Wuhan, China;Computers in Biology and Medicine;2024-08

5. Deep Learning for Pneumonia Detection in Chest X-ray Images: A Comprehensive Survey;Journal of Imaging;2024-07-23

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