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  • 标题:COVID 19 Identification in Lungs Using ArtificialIntelligence
  • 本地全文:下载
  • 作者:G.Kavitha ; DivyaPrabaR ; VellaTejaswi
  • 期刊名称:International Journal of Early Childhood Special Education
  • 电子版ISSN:1308-5581
  • 出版年度:2022
  • 卷号:14
  • 期号:4
  • 页码:385-390
  • DOI:10.9756/INT-JECSE/V14I4.48
  • 语种:English
  • 出版社:International Journal of Early Childhood Special Education
  • 摘要:COVID19 worldwide pandemic influences fitness care and life style worldwide, and its early detection is important to controlling instances spreading and mortality. The real chief prognosis check is the Reverse transcription Polymer as echain reaction(RTPCR), the result instances, and the price of those assessments are high. So we`re detecting the presence of COVID19tofindingsinChestX-rayphotographs,method makes use of present deep mastering fashions to the system those photographs and classify them as high quality or bad for COVID19. The pleasant appearing fashions most of the evaluated ones have been the Dense Net, Res Net, and Xception fashions, with the effects indicating the opportunity of figuring out COVID19 high-quality instances fromchestX-ray photographs.
  • 关键词:COVID-19;X-rays;Artificial learning;convolutional neural networks
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