A deep learning framework for COVID-19 detection: integrating attention modules into ResNet50 and optimizing cross-entropy loss function
This paper presents a tri-class classification framework for distinguishing COVID-19, viral pneumonia, and normal cases from chest X-rays, built on a pre-trained ResNet50 and incorporates CBAM attention modules at two well-justified stages.