A Simplified Convolutional Neural Network Design for COVID-19 Classification on Chest X-ray Images

DOI: 10.1109/jcsse54890.2022.9836299 Publication Date: 2022-07-28T19:47:39Z
ABSTRACT
COVID-19 is a respiratory virus that causes the spread of infection and has affected human around world. The frequently results in pneumonia which can be detected using lung imaging, chest X-ray images. Deep learning models have been demonstrated to an effective interpretation on radiography. In this paper, we proposed simplified convolutional neural network model for screening classify appearance lesion into two classes. model; despite fewer layers utilization data augmentation approach training process, achieve greater outcome. To evaluate model, used partial public dataset, Radiography Database collection 13,808 At final stage, Grad-CAM visualization method enhance important region images order provide explanations predictions.
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