R2C-GAN: Restore-to-Classify Generative Adversarial Networks for blind X-ray restoration and COVID-19 classification-Reference-Cited by-同舟云学术

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R2C-GAN: Restore-to-Classify Generative Adversarial Networks for blind X-ray restoration and COVID-19 classification

Published:2024-12 Issue: Volume:156 Page:110765
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Ahishali Mete^ORCID,Degerli Aysen,Kiranyaz Serkan,Hamid Tahir,Mazhar Rashid,Gabbouj Moncef^ORCID

Publisher

Elsevier BV

Reference38 articles.

1. Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images;Rahman;Comput. Biol. Med.,2021

2. A variational model for image classification and restoration;Samson;IEEE Trans. Pattern Anal. Mach. Intell.,2000

3. Frontal cortex neuron type classification with deep learning and recurrence plot;Özcan;Trait. du Signal,2021

4. Robust implementation of foreground extraction and vessel segmentation for X-ray coronary angiography image sequence;Fu;Pattern Recognit.,2024

5. A pyramid input augmented multi-scale CNN for GGO detection in 3D lung CT images;Liu;Pattern Recognit.,2023

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