Study and Survey Available Identification technique of COVID-19 Infection using their X-Ray Image

Authors

  • Anupam Kumar Singh  Research Scholar, SHEAT COLLEGE OF ENGINEERING, VARANASI, India
  • Shailesh Kumar Singh  SHEAT COLLEGE OF ENGINEERING, VARANASI, India

Keywords:

COVID-19 Infection, X-Ray Image, COVIDX-Net, MobileNetV2, Xception, InceptionV3, ResNetV2, DenseNet121, VGG19

Abstract

Few in the contemporary period foresaw the outbreak of pneumonia produced by the coronavirus that causes severe acute respiratory syndrome (SARS CoV-2) or coronavirus illness 2019, which began at year's end (COVID-19). Medical professionals’ worldwide struggle to keep up with the fast global spread of the COVID-19 pandemic. The disease was first detected in Wuhan, China, but has now spread to every continent. Due to the time required for diagnosis and the high cost of test kits, deep learning and artificial intelligence research and apps have been developed to help doctors treat patients battling illnesses. There is a substantial obstacle to success presented by the high cost of diagnostic laboratory kits, especially in less developed countries. Using X-ray images for automatic detection might be helpful for hospitals and governments without access to a CT scanner or a laboratory kit for detecting COVID-19. A proper diagnosis is crucial since there is currently no effective therapy available. Deep learning approaches have been used for analyzing COVID-19 CXR images. In addition, we have classified the many studies in this field into three distinct groups: COVID-19 studies in the medical field, DL works in CAD connected to COVID-19, and CAD studies related to COVID-19 via deep transfer learning. The results, proposed procedures, datasets, data preparation, and evaluation techniques have all been covered.

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International Journal of Scientific Research in Science and Technology

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Published

2022-02-05

Issue

Volume 9, Issue 1, January-February-2022

Section

Research Articles

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How to Cite

[1]
Anupam Kumar Singh, Shailesh Kumar Singh "Study and Survey Available Identification technique of COVID-19 Infection using their X-Ray Image" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 9, Issue 1, pp.475-484, January-February-2022.