XÂY DỰNG MÔ HÌNH HỌC SÂU NHẬN DẠNG NGƯỜI KHÔNG ĐEO KHẨU TRANG
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Ngày nhận bài: 10/03/22                Ngày hoàn thiện: 23/05/22                Ngày đăng: 25/05/22Tóm tắt
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[1] T. Phong, P. Phuong, T. My. "Cough reftlex: reason and mechanism” 2020-06-02. [Online]. Available: https://www.dieutri.vn/trieuchungnoi/phan-xa-ho-tai-sao-va-co-che-hinh-thanh. [Accessed Jan. 07, 2022].
[2] L. Li et al., "A review of face recognition technology," Proceedings of the IEEE/CVF International Conference on Computer Vision, access 8, 2020, pp. 139110-139120.
[3] S. -H. Lin, "An introduction to face recognition technology," Informing Sci. Int. J. an Emerg. Transdiscipl, vol. 3, pp. 1-7, 2000.
[4] K. He et al., “Deep residual learning for image recognition,” Proceedings of the IEEE/CVPR Conference on Computer Vision and Pattern Recognition, 2016, pp. 770-778.
[5] M. Tan and Q. Le, “Efficientnet: Rethinking model scaling for convolutional neural networks,” International conference on machine learning, PMLR, 2019, pp. 6105-6114.
[6] J. Redmon and A. Farhadi, “YOLO9000: better, faster, stronger,” Proceedings of the IEEE/CVPR Conference on Computer Vision and Pattern Recognition, 2017, pp. 7263-7271.
[7] T. Y. Lin et al., “Focal loss for dense object detection,” Proceedings of the IEEE/CVF International Conference on Computer Vision, 2017, pp. 2980-2988.
[8] D. Q. Vu, N. Le, and J. C. Wang, “Teaching yourself: A self-knowledge distillation approach to action recognition,” IEEE Access, vol. 9, pp. 105711-105723, 2021.
[9] D. Q. Vu et al., “A Novel Self-Knowledge Distillation Approach with Siamese Representation Learning for Action Recognition,” Proceedings of the IEEE/VCIP International Conference on Visual Communications and Image Processing, 2021, pp. 1-5.
[10] A. Howard et al., “Searching for mobilenetv3,” Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019, pp. 1314-1324.
[11] N. Ma, Ningning et al., “Shufflenet v2: Practical guidelines for efficient cnn architecture design,” Proceedings of the European conference on computer vision (ECCV), 2018, pp. 116-131.
[12] J. Deng et al., "Retinaface: Single-stage dense face localisation in the wild," Proceedings of the IEEE/CVPR Conference on Computer Vision and Pattern Recognition, 2020, pp. 5203-5212.
[13] Jain, K. Anil, and S. Z. Li, Handbook of face recognition, vol. 1. New York: Springer, 2011.
[14] Q. Luu. “Using the robot to detect human without wearing mask”, 2020. [Online]. Available: https://vnexpress.net/dung-robot-de-phat-hien-nguoi-khong-deo-khau-trang-4099618.html. [Accessed Jan. 12, 2022].
[15] "Open source library - OpenCV”, 1999. [Online]. Available: https://opencv.org/. [Accessed Jan. 12, 2022].
[16] Sakai, T., Kanade, T., Nagao, M., & Ohta, Y. I. “Picture processing system using a computer complex”, Computer Graphics and Image Processing, 2(3-4), 1973, pp. 207-215.
[17] K. Zhang et al., "Joint face detection and alignment using multitask cascaded convolutional networks," IEEE Signal Processing Letters, vol. 23, no. 10, pp. 1499-1503, 2016.
[18] S. Ioffe and C. Szegedy, "Batch normalization: Accelerating deep network training by reducing internal covariate shift," International conference on machine learning, PMLR, 2015, pp. 448-456.
[19] A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks," Advances in neural information processing systems, vol. 25, pp. 84-90, 2012.
[20] K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition," Proceedings of the International Conference on Learning Representations, 2015, pp.1-14.DOI: https://doi.org/10.34238/tnu-jst.5667
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