COVID-19 control by computer vision approaches: A survey

Anwaar Ul-Haq; Jannis Born; Asim Khan; Douglas Pinto  Sampaio Gomes; Subrata Chakraborty; Manoranjan Paul

doi:10.1109/ACCESS.2020.3027685

COVID-19 control by computer vision approaches: A survey

Anwaar Ul-Haq, Jannis Born, Asim Khan, Douglas Pinto Sampaio Gomes, Subrata Chakraborty, Manoranjan Paul

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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 language	English
Pages (from-to)	179437-179456
Number of pages	20
Journal	IEEE Access
Volume	8
DOIs	https://doi.org/10.1109/ACCESS.2020.3027685
Publication status	Published - 12 Oct 2020

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COVID-19 control by computer vision approaches: A survey

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