A Deep Learning Approach for Detecting Medical Face Mask on Human Faces in Response to Covid19
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Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-8129-5_111
Reference13 articles.
1. Ge, S., Li, J., Ye, Q. and Luo, Z.: Detecting masked faces in the wild with lle-cnns. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2682–2690 (2017)
2. Loey, M., Manogaran, G., Taha, M.H.N., Khalifa, N.E.M.: Fighting against COVID-19: a novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection. Sustainable Cities and Society, p. 102600 (2020)
3. Loey, M., Manogaran, G., Taha, M.H.N., Khalifa, N.E.M.: A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic. Measurement 167, 108288 (2020)
4. Mohan, P., Paul, A.J., Chirania, A.: A Tiny CNN Architecture for Medical Face Mask Detection for Resource-Constrained Endpoints. arXiv preprint arXiv:2011.14858 (2020)
5. Chen, S., Liu, W., Zhang, G.: Efficient transfer learning combined skip-connected structure for masked face poses classification. IEEE Access 8, 209688–209698 (2020)
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