DC-GAN-based synthetic X-ray images augmentation for increasing the performance of EfficientNet for COVID-19 detection

• Main Authors: Pir Masoom Shah, Hamid Ullah, Rahim Ullah, Dilawar Shah, Yulin Wang, Saif ul Islam, Abdullah Gani, Rodrigues, Joel J. P. C.
• Format: Article
• Language: English; English
• Published: Wiley-Blackwell Publishing 2021
• Subjects: RC581-951 Specialties of internal medicine
• Online Access: https://eprints.ums.edu.my/id/eprint/32820/1/DC-GAN-based%20synthetic%20X-ray%20images%20augmentation%20for%20increasing%20the%20performance%20of%20EfficientNet%20for%20COVID-19%20detection.pdf; https://eprints.ums.edu.my/id/eprint/32820/2/DC-GAN-based%20synthetic%20X-ray%20images%20augmentation%20for%20increasing%20the%20performance%20of%20EfficientNet%20for%20COVID-19%20detection%20_ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/32820/; https://onlinelibrary.wiley.com/doi/epdf/10.1111/exsy.12823; https://doi.org/10.1111/exsy.12823

Currently, many deep learning models are being used to classify COVID‐19 and normal cases from chest X‐rays. However, the available data (X‐rays) for COVID‐19 is limited to train a robust deep‐learning model. Researchers have used data augmentation techniques to tackle this issue by increasing the n...