Detection of Face Mask Wearing Condition for COVID-19 Using Mask R-CNN Mask R-CNN Kullanarak COVID-19 için Yüz Maskesi Takma Durumunun Tespiti
El-Cezeri Journal of Science and Engineering, cilt.9, sa.3, ss.1051-1060, 2022 (Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 9 Sayı: 3
- Basım Tarihi: 2022
- Doi Numarası: 10.31202/ecjse.1061270
- Dergi Adı: El-Cezeri Journal of Science and Engineering
- Derginin Tarandığı İndeksler: Scopus
- Sayfa Sayıları: ss.1051-1060
- Anahtar Kelimeler: Covid-19, deep learning, mask detection, mask r-cnn
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Bursa Uludağ Üniversitesi Adresli: Hayır
Özet
Due to the COVID-19 pandemic, which has affected the whole world, countries have made it mandatory for people to wear face masks. Because wearing a mask is considered one of the most effective methods to reduce the risk of transmission of the virus. However, it is difficult to manually check whether people are wearing masks. It is aimed to develop a model that detects all kinds of face masks in crowded environments using a deep neural network in this study. Mask R-CNN, which is one of the deep learning algorithms and used for object detection was used to detect and classify people’s mask states. The proposed deep learning model was trained and tested with k-fold cross-validation using a dataset of 853 images containing three classes (with mask, without a mask, incorrect use of mask). ResNet101 backbone was chosen as the backbone architecture and transfer learning was performed using the MS COCO model. The proposed Mask R-CNN model achieves a mAP of 83%, a mAR of 90%, and an F1 score of 86%. These results reveal that the proposed model is successful in mask detection.