ArticleIEEE transactions on instrumentation and measurement2021
Hybrid Transfer Learning and Broad Learning System for Wearing Mask Detection in the COVID-19 Era.
Article in IEEE transactions on instrumentation and measurement, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Beyond Flexible: Unveiling the Next Era of Flexible Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2024Review
- Deep Learning-Based Biomimetic Identification Method for Mask Wearing Standardization.Biomimetics (Basel, Switzerland) · 2024Article
- A hybrid human recognition framework using machine learning and deep neural networks.PloS one · 2024Article
- Blood pressure estimation and classification using a reference signal-less photoplethysmography signal: a deep learning framework.Physical and engineering sciences in medicine · 2023Article
- Article
- Add-on soft electronic interfaces for continuous cuffless blood pressure monitoring.Advanced materials technologies · 2023Article
- A novel attention-based enhancement framework for face mask detection in complicated scenarios.Signal processing. Image communication · 2023Article
- Autonomous face mask detection using single shot multibox detector, and ResNet-50 with identity retrieval through face matching using deep siamese neural network.Journal of ambient intelligence and humanized computing · 2023Article
- Real-time face mask position recognition system based on MobileNet model.Smart health (Amsterdam, Netherlands) · 2023Article
- Semi-Supervised KPCA-Based Monitoring Techniques for Detecting COVID-19 Infection through Blood Tests.Diagnostics (Basel, Switzerland) · 2023Article
- COVID-19 CT ground-glass opacity segmentation based on attention mechanism threshold.Biomedical signal processing and control · 2023Article
- A survey on computer vision based human analysis in the COVID-19 era.Image and vision computing · 2023Article
- Multiclass Mask Classification with a New Convolutional Neural Model and Its Real-Time Implementation.Life (Basel, Switzerland) · 2023Article
- Integration of improved YOLOv5 for face mask detector and auto-labeling to generate dataset for fighting against COVID-19.The Journal of supercomputing · 2023Article
- DTLMV2-A real-time deep transfer learning mask classifier for overcrowded spaces.Applied soft computing · 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
- STROVE: spatial data infrastructure enabled cloud-fog-edge computing framework for combating COVID-19 pandemic.Innovations in systems and software engineering · 2022Article
- A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models.Scientific reports · 2022Article
- Face Mask-Wearing Detection Model Based on Loss Function and Attention Mechanism.Computational intelligence and neuroscience · 2022Review
- Deep Generative Learning-Based 1-SVM Detectors for Unsupervised COVID-19 Infection Detection Using Blood Tests.IEEE transactions on instrumentation and measurement · 2022Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the era of Corona Virus Disease 2019 (COVID-19), wearing a mask can effectively protect people from infection risk and largely decrease the spread in public places, such as hospitals and airports. This brings a demand for the monitoring instruments that are required to detect people who are wearing masks. However, this is not the objective of existing face detection algorithms. In this article, we propose a two-stage approach to detect wearing masks using hybrid machine learning techniques. The first stage is designed to detect candidate wearing mask regions as many as possible, which is based on the transfer model of Faster_RCNN and InceptionV2 structure, while the second stage is designed to verify the real facial masks using a broad learning system. It is implemented by training a two-class model. Moreover, this article proposes a data set for wearing mask detection (WMD) that includes 7804 realistic images. The data set has 26403 wearing masks and covers multiple scenes, which is available at "https://github.com/BingshuCV/WMD." Experiments conducted on the data set demonstrate that the proposed approach achieves an overall accuracy of 97.32% for simple scene and an overall accuracy of 91.13% for the complex scene, outperforming the compared methods.
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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.