Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning
The COVID-19 pandemic has been a worldwide catastrophe. Its impact, not only economically, but also socially and in terms of human lives, was unexpected. Each of the many mechanisms to fight the contagiousness of the illness has been proven to be extremely important. One of the most important mechan...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/9/8/1050 |
| _version_ | 1797523702670163968 |
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| author | Jesús Tomás Albert Rego Sandra Viciano-Tudela Jaime Lloret |
| author_facet | Jesús Tomás Albert Rego Sandra Viciano-Tudela Jaime Lloret |
| author_sort | Jesús Tomás |
| collection | DOAJ |
| description | The COVID-19 pandemic has been a worldwide catastrophe. Its impact, not only economically, but also socially and in terms of human lives, was unexpected. Each of the many mechanisms to fight the contagiousness of the illness has been proven to be extremely important. One of the most important mechanisms is the use of facemasks. However, the wearing the facemasks incorrectly makes this prevention method useless. Artificial Intelligence (AI) and especially facial recognition techniques can be used to detect misuses and reduce virus transmission, especially indoors. In this paper, we present an intelligent method to automatically detect when facemasks are being worn incorrectly in real-time scenarios. Our proposal uses Convolutional Neural Networks (CNN) with transfer learning to detect not only if a mask is used or not, but also other errors that are usually not taken into account but that may contribute to the virus spreading. The main problem that we have detected is that there is currently no training set for this task. It is for this reason that we have requested the participation of citizens by taking different selfies through an app and placing the mask in different positions. Thus, we have been able to solve this problem. The results show that the accuracy achieved with transfer learning slightly improves the accuracy achieved with convolutional neural networks. Finally, we have also developed an Android-app demo that validates the proposal in real scenarios. |
| first_indexed | 2024-03-10T08:46:46Z |
| format | Article |
| id | doaj.art-57b0bf508f7f452e9c736707c4083f00 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-10T08:46:46Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-57b0bf508f7f452e9c736707c4083f002023-11-22T07:50:09ZengMDPI AGHealthcare2227-90322021-08-0198105010.3390/healthcare9081050Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer LearningJesús Tomás0Albert Rego1Sandra Viciano-Tudela2Jaime Lloret3Instituto de Investigacion Para la Gestion Integrada de Zonas Costeras, Universitat Politecnica de Valencia, C/Paranimf 1, Grao de Gandia, 46730 Valencia, SpainInstituto de Investigacion Para la Gestion Integrada de Zonas Costeras, Universitat Politecnica de Valencia, C/Paranimf 1, Grao de Gandia, 46730 Valencia, SpainInstituto de Investigacion Para la Gestion Integrada de Zonas Costeras, Universitat Politecnica de Valencia, C/Paranimf 1, Grao de Gandia, 46730 Valencia, SpainInstituto de Investigacion Para la Gestion Integrada de Zonas Costeras, Universitat Politecnica de Valencia, C/Paranimf 1, Grao de Gandia, 46730 Valencia, SpainThe COVID-19 pandemic has been a worldwide catastrophe. Its impact, not only economically, but also socially and in terms of human lives, was unexpected. Each of the many mechanisms to fight the contagiousness of the illness has been proven to be extremely important. One of the most important mechanisms is the use of facemasks. However, the wearing the facemasks incorrectly makes this prevention method useless. Artificial Intelligence (AI) and especially facial recognition techniques can be used to detect misuses and reduce virus transmission, especially indoors. In this paper, we present an intelligent method to automatically detect when facemasks are being worn incorrectly in real-time scenarios. Our proposal uses Convolutional Neural Networks (CNN) with transfer learning to detect not only if a mask is used or not, but also other errors that are usually not taken into account but that may contribute to the virus spreading. The main problem that we have detected is that there is currently no training set for this task. It is for this reason that we have requested the participation of citizens by taking different selfies through an app and placing the mask in different positions. Thus, we have been able to solve this problem. The results show that the accuracy achieved with transfer learning slightly improves the accuracy achieved with convolutional neural networks. Finally, we have also developed an Android-app demo that validates the proposal in real scenarios.https://www.mdpi.com/2227-9032/9/8/1050facemask-wearing conditiontransfer learningconvolutional neural networkdeep learningfacial recognitionCOVID-19 |
| spellingShingle | Jesús Tomás Albert Rego Sandra Viciano-Tudela Jaime Lloret Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning Healthcare facemask-wearing condition transfer learning convolutional neural network deep learning facial recognition COVID-19 |
| title | Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning |
| title_full | Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning |
| title_fullStr | Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning |
| title_full_unstemmed | Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning |
| title_short | Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning |
| title_sort | incorrect facemask wearing detection using convolutional neural networks with transfer learning |
| topic | facemask-wearing condition transfer learning convolutional neural network deep learning facial recognition COVID-19 |
| url | https://www.mdpi.com/2227-9032/9/8/1050 |
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