Repository logo
  • English
  • Español
  • Log In
    Have you forgotten your password?
Universidad Tecnológica Indoamérica
Repository logo
  • Communities & Collections
  • Research Outputs
  • Projects
  • Researchers
  • Statistics
  • Investigación Indoamérica
  • English
  • Español
  • Log In
    Have you forgotten your password?
  1. Home
  2. CRIS
  3. Publications
  4. Facial recognition system for people with and without face mask in times of the covid-19 pandemic
 
Options

Facial recognition system for people with and without face mask in times of the covid-19 pandemic

Journal
Sustainability (Switzerland)
Date Issued
2021
Author(s)
Talahua J.S.
Buele, Jorge
Facultad de Ingenierías
Calvopina P.
Varela Aldas, José
Centro de Investigación de Ciencias Humanas y de la Educación
Type
Article
DOI
10.3390/su13126900
URL
https://cris.indoamerica.edu.ec/handle/123456789/8689
Abstract
In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv's face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Subjects
  • teaching evaluation; ...

Scopus© citations
44
Acquisition Date
Jun 6, 2024
View Details
Article has an altmetric score of 2
altmetric
dimensions
Views
2
Acquisition Date
May 21, 2025
View Details
google-scholar
Downloads
Logo Universidad Tecnológica Indoamérica Hosting and Support by Logo Scimago

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback

We collect and process your personal information for the following purposes: Authentication, Preferences, Acknowledgement and Statistics.
To learn more, please read our
privacy policy.

Customize
Posted by 3 X users
164 readers on Mendeley
See more details