ArticleJournal of biomedical informatics2021
Face mask detection using deep learning: An approach to reduce risk of Coronavirus spread.
Article in Journal of biomedical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 210 citations in OpenAlex.
- A Review on Face Mask Recognition.Sensors (Basel, Switzerland) · 2025Review
- Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.The Indian journal of medical research · 2025Article
- Deep Learning-Based Object Detection Strategies for Disease Detection and Localization in Chest X-Ray Images.Diagnostics (Basel, Switzerland) · 2024Article
- FMDNet: An Efficient System for Face Mask Detection Based on Lightweight Model during COVID-19 Pandemic in Public Areas.Sensors (Basel, Switzerland) · 2023Article
- CoSumNet: A video summarization-based framework for COVID-19 monitoring in crowded scenes.Artificial intelligence in medicine · 2023Article
- Artificial Intelligence: A Next-Level Approach in Confronting the COVID-19 Pandemic.Healthcare (Basel, Switzerland) · 2023Review
- Ensemble of deep transfer learning models for real-time automatic detection of face mask.Multimedia tools and applications · 2023Article
- Face mask detection and social distance monitoring system for COVID-19 pandemic.Multimedia tools and applications · 2023Article
- AI-based face mask detection system: a straightforward proposition to fight with Covid-19 situation.Multimedia tools and applications · 2023Article
- Comparative analysis of deep learning models for detecting face mask.Procedia computer science · 2023Article
- A Unified Framework for Monitoring Social Distancing and Face Mask Wearing Using Deep Learning: An Approach to Reduce COVID-19 Risk.Procedia computer science · 2023Article
- Mask images on Twitter increase during COVID-19 mandates, especially in Republican counties.Scientific reports · 2022Article
- Deep transfer learning for the recognition of types of face masks as a core measure to prevent the transmission of COVID-19.Applied soft computing · 2022Article
- A Novel Efficient Convolutional Neural Algorithm for Multi-Category Aliasing Hardware Recognition.Sensors (Basel, Switzerland) · 2022Article
- Novel informatics approaches to COVID-19 Research: From methods to applications.Journal of biomedical informatics · 2022Article
- Heart rate prediction from facial video with masks using eye location and corrected by convolutional neural networks.Biomedical signal processing and control · 2022Article
- An Efficient and Effective Deep Learning-Based Model for Real-Time Face Mask Detection.Sensors (Basel, Switzerland) · 2022Article
- Deep Learning Models for Multiple Face Mask Detection under a Complex Big Data Environment.Procedia computer science · 2022Article
- Face detection for rail transit passengers based on single shot detector and active learning.Multimedia tools and applications · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effective strategies to restrain COVID-19 pandemic need high attention to mitigate negatively impacted communal health and global economy, with the brim-full horizon yet to unfold. In the absence of effective antiviral and limited medical resources, many measures are recommended by WHO to control the infection rate and avoid exhausting the limited medical resources. Wearing a mask is among the non-pharmaceutical intervention measures that can be used to cut the primary source of SARS-CoV2 droplets expelled by an infected individual. Regardless of discourse on medical resources and diversities in masks, all countries are mandating coverings over the nose and mouth in public. To contribute towards communal health, this paper aims to devise a highly accurate and real-time technique that can efficiently detect non-mask faces in public and thus, enforcing to wear mask. The proposed technique is ensemble of one-stage and two-stage detectors to achieve low inference time and high accuracy. We start with ResNet50 as a baseline and applied the concept of transfer learning to fuse high-level semantic information in multiple feature maps. In addition, we also propose a bounding box transformation to improve localization performance during mask detection. The experiment is conducted with three popular baseline models viz. ResNet50, AlexNet and MobileNet. We explored the possibility of these models to plug-in with the proposed model so that highly accurate results can be achieved in less inference time. It is observed that the proposed technique achieves high accuracy (98.2%) when implemented with ResNet50. Besides, the proposed model generates 11.07% and 6.44% higher precision and recall in mask detection when compared to the recent public baseline model published as RetinaFaceMask detector. The outstanding performance of the proposed model is highly suitable for video surveillance devices.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.