یک رویکرد یادگیری انتقالی با شبکه عصبی کانولوشنال برای تشخیص افراد دارای ماسک از روی تصاویر

[1] Cabani, K. Hammoudi, H. Benhabiles, and M. Melkemi, "MaskedFace-Net–A dataset of correctly/incorrectly masked face images in the context of COVID-19." Smart Health, vol.19, 2021.

[2] V. Militante and N. V. Dionisio, "Real-Time Facemask Recognition with Alarm System using Deep Learning," 2020 11th IEEE Control and System Graduate Research Colloquium (ICSGRC) , pp. 106-110. IEEE, 2020

[3] J. Chowdary, N. S. Punn, S. K. Sonbhadra, and S. Agarwal, “Face mask detection using transfer learning of InceptionV3,” International Conference on Big Data Analytics , pp. 81-90 Springer, Cham, 2020.

[4] Loey, G. Manogaran, M. Hamed, N. Taha, N. Eldeen, and M. Khalifa, Fighting Against COVID-19: A Novel Deep Learning Model Based on YOLOv2 with ResNet-50 for Medical Face Mask Detection” Sustainable cities and society, vol.65, 2021

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[11] Loey, G. Manogaran, M. H. N. Taha, and N. E. M. Khalifa, “A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic,” Measurement (Lond.), vol. 167, no. 108288, p. 108288, 2021.

[12] Nagrath, R. Jain, A. Madan, R. Arora, P. Kataria, and J. Hemanth, “SSDMNV2: A real time DNN-based face mask detection system using single shot multibox detector and MobileNetV2,” Sustain. Cities Soc., vol. 66, no. 102692, p. 102692, 2021.

[13] Jiang, F. Xinqi, and Y. Hong. "Retinamask: A face mask detector." arXiv preprint arXiv:2005.03950, 2020.

[14] Ud Din, K. Javed, S. Bae, and J. Yi, “A novel GAN-based network for unmasking of masked face,” IEEE Access, vol. 8, pp. 44276–44287, 2020.

[15] I. Eyiokur, H. K. Ekenel, and A. Waibel, “Unconstrained face-mask & face-hand datasets: Building a computer vision system to help prevent the transmission of COVID-19,” arXiv preprint arXiv:2103.08773, 2021.

[16] S. Ejaz and M. R. Islam, "Masked Face Recognition Using Convolutional Neural Network," 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), pp. 1-6, 2019

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[18] Vasan, M. Alazab, S. Wassan, H. Naeem, B. Safaei, and Q. Zheng, “IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecture,” Comput. netw., vol. 171, no. 107138, p. 107138, 2020.

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[23] Weiss, T. M. Khoshgoftaar, and D. Wang, “A survey of transfer learning,” J. Big Data, vol. 3, no. 1, 2016.

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[25] Liu, C. Wang, Y. Hu, Z. Zeng, J. Bai, and G. Liao, “Transfer learning with convolutional neural network for early gastric cancer classification on magnifiying narrow-band imaging images,” In 2018 25th IEEE International Conference on Image Processing (ICIP), pp. 1388-1392. IEEE, 2018.

[26] Arjmand, S. Meshgini and R. Afrouzian, Breast tumor detection using convolutional neural network in MRI images, Journal of Advances Signal Processing, vol. 3, no. 2, pp. 109-117, 2019

[27] M. Peyrohoseini nejad, A. Karami, Automatic small defect detection in unmanned aerial vehicle images of power transmission lines using DRSPTL, Journal of Advances Signal Processing, vol. 4, no. 2, 159-170, 2020.