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COVID-19 Control by Computer Vision Approaches: A Survey
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 contribut...
Formato: | Online Artículo Texto |
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Lenguaje: | English |
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IEEE
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545281/ https://www.ncbi.nlm.nih.gov/pubmed/34812357 http://dx.doi.org/10.1109/ACCESS.2020.3027685 |
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collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8545281 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | IEEE |
record_format | MEDLINE/PubMed |
spelling | pubmed-85452812021-11-18 COVID-19 Control by Computer Vision Approaches: A Survey IEEE Access Imaging 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. IEEE 2020-09-29 /pmc/articles/PMC8545281/ /pubmed/34812357 http://dx.doi.org/10.1109/ACCESS.2020.3027685 Text en This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Imaging COVID-19 Control by Computer Vision Approaches: A Survey |
title | COVID-19 Control by Computer Vision Approaches: A Survey |
title_full | COVID-19 Control by Computer Vision Approaches: A Survey |
title_fullStr | COVID-19 Control by Computer Vision Approaches: A Survey |
title_full_unstemmed | COVID-19 Control by Computer Vision Approaches: A Survey |
title_short | COVID-19 Control by Computer Vision Approaches: A Survey |
title_sort | covid-19 control by computer vision approaches: a survey |
topic | Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545281/ https://www.ncbi.nlm.nih.gov/pubmed/34812357 http://dx.doi.org/10.1109/ACCESS.2020.3027685 |
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