R2C-GAN: Restore-to-Classify GANs for Blind X-Ray Restoration and COVID-19 Classification. (arXiv:2209.14770v1 [eess.IV])

Restoration of poor quality images with a blended set of artifacts plays a
vital role for a reliable diagnosis. Existing studies have focused on specific
restoration problems such as image deblurring, denoising, and exposure
correction where there is usually a strong assumption on the artifact type and
severity. As a pioneer study in blind X-ray restoration, we propose a joint
model for generic image restoration and classification: Restore-to-Classify
Generative Adversarial Networks (R2C-GANs). Such a jointly optimized model
keeps any disease …

arxiv classification covid covid-19 gan gans ray restore x-ray