Mask Detection From Face Images Using Deep Learning and Transfer Learning
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Date
2021
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
It is vital important for people to wear masks during the pandemic that affects the whole world. In this study, it was detected whether people wear masks by using convolutional neural networks which is one of the deep learning methods and transfer learning. In the classification carried out using the Resnet-18 architecture, both real-life images obtained with the Huawei M2150 camera and images shared as open source were used. The system, which was trained using 18600 images, was tested with 4540 real-world images and 95.16% sensitivity 96.69% specificity values were obtained. Thus, a model that works with high performance not only on high resolution images taken close up, but also on low resolution images taken from afar was obtained. © 2021 IEEE.
Description
15th Turkish National Software Engineering Symposium, UYMS 2021 -- 17 November 2021 through 19 November 2021 -- -- 176220
Keywords
deep learning, mask detection, transfer learning, Convolutional neural networks, Face recognition, Transfer learning, Wear of materials, Convolutional neural network, Deep learning, Face images, Learning methods, Learning Transfer, Mask detection, Open-source, Real-life images, Real-world image, Transfer learning, Deep learning
Turkish CoHE Thesis Center URL
Fields of Science
Citation
WoS Q
N/A
Scopus Q
N/A

OpenCitations Citation Count
2
Source
2021 Turkish National Software Engineering Symposium, UYMS 2021 - Proceedings
Volume
Issue
Start Page
1
End Page
4
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Citations
CrossRef : 2
Scopus : 4
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Mendeley Readers : 3
SCOPUS™ Citations
4
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