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Title: Mask Detection from Face Images Using Deep Learning and Transfer Learning
Authors: Örnek, Ahmet Haydar
Çelik, Mustafa
Ceylan, Murat
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
Real-life images
Real-world image
Transfer learning
Deep learning
Issue Date: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
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
ISBN: 9781665410700
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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