Frontiers in Signal Processing

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DOI: 10.22606/fsp.2021.51001

• Fan Liu
  College of Electrical & Information Engineering, Southwest Minzu University, Chendu, 610041, China
• Wei Xiang^*
  College of Electrical & Information Engineering, Southwest Minzu University, Chendu, 610041, China
• Li Wang
  College of Electrical & Information Engineering, Southwest Minzu University, Chendu, 610041, China
• Jintao Zhang
  College of Electrical & Information Engineering, Southwest Minzu University, Chendu, 610041, China
• Jiacheng Li
  College of Electrical & Information Engineering, Southwest Minzu University, Chendu, 610041, China

Corona Virus Disease 2019 (COVID-19) is an acute respiratory infection caused by the 2019 novel coronavirus infection that was discovered in some hospitals in Wuhan, China in December 2019. From a global perspective, COVID-19 epidemic is still in a pandemic period. Every country is taking timely preventive measures. Therefore, it is necessary to use Artificial Intelligence (AI) identification to assist radiologists in diagnosing COVID-19. This paper proposes a network model of dynamic self-attention machine for pneumonia images. The model adopts DPN92 and GCNet. It implements CR images and CT image classification of COVID-19. A COVID-19 detection system based on dynamic auto-attention machine is designed. The lung CT or CR images that meet the design requirements will be uploaded through the browser, and the background server will analyze and process the lung images, and finally output the detection category of the lung images.

B/S model, SRGAN, GCNet, DPN92, COVID-19, CR, CT, image classification.

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