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A Survey on Deep Transfer Learning to Edge Computing for Mitigating the COVID-19 Pandemic
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  • Abu Sufian ,
  • Anirudha Ghosh ,
  • Ali Safaa Sadiq ,
  • Florentin Smarandache
Abu Sufian
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Anirudha Ghosh
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Ali Safaa Sadiq
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Florentin Smarandache
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Highlights of the article are:
• Presented a systematic study of Deep Learning (DL), Deep Transfer Learning (DTL) and Edge Computing(EC) to mitigate COVID-19.
• Surveyed on existing DL, DTL, EC, and Dataset to mitigate pandemics with potentialities and challenges.
• Drawn a precedent pipeline model of DTL over EC for a future scope to mitigate any outbreaks.
• Given brief analyses and challenges wherever relevant in perspective of COVID-19.
Sep 2020Published in Journal of Systems Architecture volume 108 on pages 101830. 10.1016/j.sysarc.2020.101830