ORIGINAL RESEARCH article

Front. Public Health, 07 March 2022

Sec. Digital Public Health

Volume 10 - 2022 | https://doi.org/10.3389/fpubh.2022.855254

RETRACTED: Facial Mask Detection Using Depthwise Separable Convolutional Neural Network Model During COVID-19 Pandemic

  • 1. Center for Research & Innovation, CoRI, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia

  • 2. Institute of Computing and Information Technology, Gomal University, Dera Ismail Khan, Pakistan

  • 3. Computer Sciences Program, Turabah University College, Taif University, Taif, Saudi Arabia

  • 4. Research Chair of Pervasive and Mobile Computing, Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

  • 5. Faculty of Pharmacy, Gomal University, Dera Ismail Khan, Pakistan

  • 6. Faculty of Computing, Riphah International University, Islamabad, Pakistan

  • 7. Malaysian Institute of Information Technology, University of Kuala Lumpur, Kuala Lumpur, Malaysia

  • 8. Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia

  • 9. Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia

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This article has been retracted. Please follow the link to the full retraction notice for details.

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Citation

Asghar MZ, Albogamy FR, Al-Rakhami MS, Asghar J, Rahmat MK, Alam MM, Lajis A and Nasir HM (2022) RETRACTED: Facial Mask Detection Using Depthwise Separable Convolutional Neural Network Model During COVID-19 Pandemic. Front. Public Health 10:855254. doi: 10.3389/fpubh.2022.855254

Received

15 January 2022

Accepted

31 January 2022

Published

07 March 2022

Volume

10 - 2022

Edited by

Thippa Reddy Gadekallu, VIT University, India

Reviewed by

Praveen Kumar, VIT University, India; Muhammad Shuaib Qureshi, University of Central Asia, Kyrgyzstan; Muhammad Fayaz, Jeju National University, South Korea

Updates

This article was submitted to Digital Public Health, a section of the journal Frontiers in Public Health

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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