Örnek, Ahmet HaydarÇelik, MustafaCeylan, Murat2022-05-232022-05-2320219781665410700https://doi.org/10.1109/UYMS54260.2021.9659582https://hdl.handle.net/20.500.13091/238115th Turkish National Software Engineering Symposium, UYMS 2021 -- 17 November 2021 through 19 November 2021 -- -- 176220It 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.eninfo:eu-repo/semantics/closedAccessdeep learningmask detectiontransfer learningConvolutional neural networksFace recognitionTransfer learningWear of materialsConvolutional neural networkDeep learningFace imagesLearning methodsLearning TransferMask detectionOpen-sourceReal-life imagesReal-world imageTransfer learningDeep learningConference Object10.1109/UYMS54260.2021.96595822-s2.0-85124797403