Multi-Disease Classification of COVID-19 in Chest Radiographs using Ensemble of Optimized Deep Learning Models-Reference-Cited by-同舟云学术

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Multi-Disease Classification of COVID-19 in Chest Radiographs using Ensemble of Optimized Deep Learning Models

Published:2023-10-28 Issue: Volume: Page:
ISSN:
Container-title:2023 15th Biomedical Engineering International Conference (BMEiCON)
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Author:

Bui Toan Huy¹,Hamamoto Kazuhiko²,Bui Linh Khanh³,Paing May Phu⁴

Affiliation:

1. Tokai University,College of Science and Technology,Kanagawa,Japan,259-1292

2. Tokai University,Graduate School of Information and Telecommunication Engineering,Tokyo,Japan,108-8619

3. Electric Power University,Faculty of Information Technology,Hanoi,Vietnam

4. King Mongkut’s Institute of Technology Ladkrabang,School of Engineering,Bangkok,Thailand,10520

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10321955/10321820/10321967.pdf?arnumber=10321967

Reference23 articles.

1. A Novel Multi-stage Residual Feature Fusion Network for Detection of COVID-19 in Chest X-ray Images

2. Fast objective & duality gap convergence for nonconvex-strongly-concave min-max problems;guo,2020

3. Deep Learning Approaches for Detecting COVID-19 From Chest X-Ray Images: A Survey

4. Deep-Precognitive Diagnosis: Preventing Future Pandemics by Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network

5. Radiology Department Preparedness for COVID-19: Radiology Scientific Expert Review Panel

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