Face Mask Detection on Single-Face and Multi-Face Video Using Convolutional Neural Network

Dini Adni Navastara*, Jeremy Vijay Wongso, Chastine Fatichah

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays, coronavirus disease has become more widespread. The virus is able to attack the human respiratory function. One of the ways to decrease the virus spread is to wear a face mask correctly in a public place. This paper proposed a RetinaFace for detecting a face and Convolutional Neural Network for classifying a face mask. The experimental dataset contains single-face and multi-face videos recorded using a drone camera. Based on the test results, NASNetMobile architecture yields the best performance with accuracy, precision, recall, and f1-score of 82.76%, 100%, 78.72%, 88.09%, respectively.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Advanced Technology and Multidiscipline, ICATAM 2021
Subtitle of host publication"Advanced Technology and Multidisciplinary Prospective Towards Bright Future" Faculty of Advanced Technology and Multidiscipline
EditorsPrihartini Widiyanti, Prastika Krisma Jiwanti, Gunawan Setia Prihandana, Ratih Ardiati Ningrum, Rizki Putra Prastio, Herlambang Setiadi, Intan Nurul Rizki
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735444423
DOIs
Publication statusPublished - 19 May 2023
Event1st International Conference on Advanced Technology and Multidiscipline: Advanced Technology and Multidisciplinary Prospective Towards Bright Future, ICATAM 2021 - Virtual, Online
Duration: 13 Oct 202114 Oct 2021

Publication series

NameAIP Conference Proceedings
Volume2536
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference1st International Conference on Advanced Technology and Multidiscipline: Advanced Technology and Multidisciplinary Prospective Towards Bright Future, ICATAM 2021
CityVirtual, Online
Period13/10/2114/10/21

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