A Deep Learning Approach for Face Mask Detection
2nd International Conference on Intelligent and Cloud Computing, ICICC 2021
; 286:295-303, 2022.
Article
in English
| Scopus | ID: covidwho-1826296
ABSTRACT
The whole world is passing through a very difficult time since the outbreak of Covid-19. Wave after wave of this pandemic hitting people very hard across the globe. We have lost around 3.8 million lives so far to this pandemic. Moreover, the impact of this pandemic and the pandemic-induced lockdown on the lives and livelihoods of the people in the developing world is very significant. Till now there is no one-shot remedy available to stop this pandemic. However, spread can be controlled by social distancing, frequent hand sanitization, and using a face mask in public places. So, in this paper, we proposed a model to detect face mask of people in public places. The proposed model uses OpenCv module to pre-process the input images, it then uses a deep learning classifier MobileNetV3 for face mask detection. The accuracy of the proposed model is almost 97%. The proposed model is very light and can be installed on any mobile or embedded system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2nd International Conference on Intelligent and Cloud Computing, ICICC 2021
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS