X-Ray image-based COVID-19 detection using deep learning

• Published in: Multimedia tools and applications Vol. 82; no. 28; pp. 44507 - 44525
• Main Authors: Ayalew, Aleka Melese, Salau, Ayodeji Olalekan, Tamyalew, Yibeltal, Abeje, Bekalu Tadele, Woreta, Nigus
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2023; Springer Nature B.V
• Subjects: Accuracy; Artificial neural networks; Chest; Computer Communication Networks; Computer Science; COVID-19; Data Structures and Information Theory; Deep learning; Disease transmission; Image acquisition; Image classification; Image segmentation; Image transmission; Machine learning; Medical imaging; Model accuracy; Multimedia Information Systems; Special Purpose and Application-Based Systems; Track 2: Medical Applications of Multimedia; COVID-19; Deep learning; CNN; Image processing; Chest X-ray; Classification

COVID-19 is a type of respiratory infection that primarily affects the lungs. Obtaining a chest X-ray is one of the most important steps in detecting and treating COVID-19 occurrences. Our study's goal is to detect COVID-19 from chest X-ray images using a Convolutional Neural Network (CNN). Thi...