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COVID-19 Control by Computer Vision Approaches: A Survey

  • Anwaar Ulhaq
  • , Jannis Born
  • , Asim Khan
  • , Douglas Pinto Sampaio Gomes
  • , Subrata Chakraborty
  • , Manoranjan Paul

Research output: Contribution to journalArticlepeer-review

96 Citations (Scopus)

Abstract

The COVID-19 pandemic has triggered an urgent call to contribute to the fight against an immense threat to the human population. Computer Vision, as a subfield of artificial intelligence, has enjoyed recent success in solving various complex problems in health care and has the potential to contribute to the fight of controlling COVID-19. In response to this call, computer vision researchers are putting their knowledge base at test to devise effective ways to counter COVID-19 challenge and serve the global community. New contributions are being shared with every passing day. It motivated us to review the recent work, collect information about available research resources, and an indication of future research directions. We want to make it possible for computer vision researchers to find existing and future research directions. This survey article presents a preliminary review of the literature on research community efforts against COVID-19 pandemic.

Original languageEnglish
Pages (from-to)179437-179456
JournalIEEE Access
Volume8
Early online date29 Sept 2020
DOIs
Publication statusPublished - 12 Oct 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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