COVID-19 Control by Computer Vision Approaches: A Survey

IEEE Access. 2020 Sep 29:8:179437-179456. doi: 10.1109/ACCESS.2020.3027685. eCollection 2020.

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.

Keywords: Artificial intelligence; COVID-19; computer vision; review; survey.

Associated data

  • figshare/10.6084/m9.figshare

Grants and funding

This work was supported by Charles Sturt University, COVID-19 Fund.