Masked Face Recognition Using Deep Learning: A Review

A large number of intelligent models for masked face recognition (MFR) has been recently presented and applied in various fields, such as masked face tracking for people safety or secure authentication. Exceptional hazards such as pandemics and frauds have noticeably accelerated the abundance of rel...

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Autores principales:	Ahmad Alzu’bi, Firas Albalas, Tawfik AL-Hadhrami, Lojin Bani Younis, Amjad Bashayreh
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	masked face recognition deep learning neural networks occluded face detection secure authentication Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/056df68ef28f4424a4aea8b7c50fe580
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spelling	oai:doaj.org-article:056df68ef28f4424a4aea8b7c50fe5802021-11-11T15:39:38ZMasked Face Recognition Using Deep Learning: A Review10.3390/electronics102126662079-9292https://doaj.org/article/056df68ef28f4424a4aea8b7c50fe5802021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2666https://doaj.org/toc/2079-9292A large number of intelligent models for masked face recognition (MFR) has been recently presented and applied in various fields, such as masked face tracking for people safety or secure authentication. Exceptional hazards such as pandemics and frauds have noticeably accelerated the abundance of relevant algorithm creation and sharing, which has introduced new challenges. Therefore, recognizing and authenticating people wearing masks will be a long-established research area, and more efficient methods are needed for real-time MFR. Machine learning has made progress in MFR and has significantly facilitated the intelligent process of detecting and authenticating persons with occluded faces. This survey organizes and reviews the recent works developed for MFR based on deep learning techniques, providing insights and thorough discussion on the development pipeline of MFR systems. State-of-the-art techniques are introduced according to the characteristics of deep network architectures and deep feature extraction strategies. The common benchmarking datasets and evaluation metrics used in the field of MFR are also discussed. Many challenges and promising research directions are highlighted. This comprehensive study considers a wide variety of recent approaches and achievements, aiming to shape a global view of the field of MFR.Ahmad Alzu’biFiras AlbalasTawfik AL-HadhramiLojin Bani YounisAmjad BashayrehMDPI AGarticlemasked face recognitiondeep learningneural networksoccluded face detectionsecure authenticationElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2666, p 2666 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	masked face recognition deep learning neural networks occluded face detection secure authentication Electronics TK7800-8360
spellingShingle	masked face recognition deep learning neural networks occluded face detection secure authentication Electronics TK7800-8360 Ahmad Alzu’bi Firas Albalas Tawfik AL-Hadhrami Lojin Bani Younis Amjad Bashayreh Masked Face Recognition Using Deep Learning: A Review
description	A large number of intelligent models for masked face recognition (MFR) has been recently presented and applied in various fields, such as masked face tracking for people safety or secure authentication. Exceptional hazards such as pandemics and frauds have noticeably accelerated the abundance of relevant algorithm creation and sharing, which has introduced new challenges. Therefore, recognizing and authenticating people wearing masks will be a long-established research area, and more efficient methods are needed for real-time MFR. Machine learning has made progress in MFR and has significantly facilitated the intelligent process of detecting and authenticating persons with occluded faces. This survey organizes and reviews the recent works developed for MFR based on deep learning techniques, providing insights and thorough discussion on the development pipeline of MFR systems. State-of-the-art techniques are introduced according to the characteristics of deep network architectures and deep feature extraction strategies. The common benchmarking datasets and evaluation metrics used in the field of MFR are also discussed. Many challenges and promising research directions are highlighted. This comprehensive study considers a wide variety of recent approaches and achievements, aiming to shape a global view of the field of MFR.
format	article
author	Ahmad Alzu’bi Firas Albalas Tawfik AL-Hadhrami Lojin Bani Younis Amjad Bashayreh
author_facet	Ahmad Alzu’bi Firas Albalas Tawfik AL-Hadhrami Lojin Bani Younis Amjad Bashayreh
author_sort	Ahmad Alzu’bi
title	Masked Face Recognition Using Deep Learning: A Review
title_short	Masked Face Recognition Using Deep Learning: A Review
title_full	Masked Face Recognition Using Deep Learning: A Review
title_fullStr	Masked Face Recognition Using Deep Learning: A Review
title_full_unstemmed	Masked Face Recognition Using Deep Learning: A Review
title_sort	masked face recognition using deep learning: a review
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/056df68ef28f4424a4aea8b7c50fe580
work_keys_str_mv	AT ahmadalzubi maskedfacerecognitionusingdeeplearningareview AT firasalbalas maskedfacerecognitionusingdeeplearningareview AT tawfikalhadhrami maskedfacerecognitionusingdeeplearningareview AT lojinbaniyounis maskedfacerecognitionusingdeeplearningareview AT amjadbashayreh maskedfacerecognitionusingdeeplearningareview
_version_	1718434518107422720

Masked Face Recognition Using Deep Learning: A Review

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