Ulhaq Anwaar, Born Jannis, Khan Asim, Gomes Douglas Pinto Sampaio, Chakraborty Subrata, Paul Manoranjan
School of Computing and MathematicsCharles Sturt University Port Macquarie NSW 2795 Australia.
Department for Biosystems Science and EngineeringETH Zurich 4058 Basel Switzerland.
IEEE Access. 2020 Sep 29;8:179437-179456. doi: 10.1109/ACCESS.2020.3027685. eCollection 2020.
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.
新冠疫情引发了为抗击这一人类巨大威胁做出贡献的紧急呼吁。计算机视觉作为人工智能的一个子领域，最近在解决医疗保健中的各种复杂问题方面取得了成功，并且有潜力为控制新冠疫情的斗争做出贡献。响应这一呼吁，计算机视觉研究人员正在检验他们的知识库，以设计出应对新冠疫情挑战的有效方法，并为全球社会服务。新的贡献与日俱增。这促使我们回顾近期的工作，收集有关现有研究资源的信息，并指明未来的研究方向。我们希望让计算机视觉研究人员能够找到现有的和未来的研究方向。这篇综述文章对研究界抗击新冠疫情的努力的文献进行了初步回顾。
