N. A. Andriyanov and V. E. Dementiev, “Developing and studying the algorithm for segmentation of simple images using detectors based on doubly stochastic random fields,” Pattern Recognit. Image Anal. 29 (1), 1–9 (2019). https://doi.org/10.1134/S105466181901005X
N. Andriyanov, V. Dementev, A. Tashlinskiy, and K. Vasiliev, “The study of improving the accuracy of convolutional neural networks in face recognition tasks,” Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021, Ed. by A. Del Bimbo (Springer, Cham, 2021), pp. 5–14. https://doi.org/10.1007/978-3-030-68821-9_1
N. A. Andriyanov, K. K. Vasiliev, and V. E. Dementiev, “Anomalies detection on spatially inhomogeneous polyzonal images,” CEUR Workshop Proc. 1901, 10–15 (2017). https://doi.org/10.18287/1613-0073-2017-1901-10-15
N. A. Andriyanov and D. A. Andriyanov, “The using of data augmentation in machine learning in image processing tasks in the face of data scarcity,” J. Phys.: Conf. Ser. 1661 (1), 012018 (2020).
B. B. Traore, B. Kamsu-Foguem, and F. Tangara, “Deep convolution neural network for image recognition,” Ecol. Inf. 48, 257–268 (2018). https://doi.org/10.1016/j.ecoinf.2018.10.002
A. Buslaev, A. Parinov, E. Khvedchenya, V. Iglovikov, and A. Kalinin, “Albumentations: Fast and flexible image augmentations,” arXiv (2018). arXiv:1809.06839v1 [cs.CV]
M. Coşkun, A. Uçar, Ö. Yıldırım, and Y. Demir, “Face recognition based on convolutional neural network,” in International Conference on Modern Electrical and Energy Systems (IEEE, 2017). https://doi.org/10.1109/MEES.2017.8248937
Guillaume Dave, Xing Chao, and Kishore Sriadibhatla, Face Recognition in Mobile Phones (Stanford Univ., 2010).
V. E. Dementyiev, N. A. Andriyanov, and K. K. Vasilyiev, “Use of images augmentation and implementation of doubly stochastic models for improving accuracy of recognition algorithms based on convolutional neural networks,” in 2020 Systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2020 (IEEE, 2020). https://doi.org/10.1109/SYNCHROINFO49631.2020.9166000
Geng Du, Fei Su, and Anni Cai, “Face recognition using SURF features,” in Proceedings of SPIE–The International Society for Optical Engineering (2009). https://doi.org/10.1117/12.832636
https://www.kaggle.com/c/dogs-vs-cats. Accessed March 24, 2021.
M. Fox, “Facial recognition tech secures enterprise access control,” Biom. Technol. Today 2017 (10), 2–3 (2017). https://doi.org/10.1016/S0969-4765(17)30145-5
Ye Li, Yinghui Wang, Jing Liu, and Wen Hao, “Expression-insensitive 3D face recognition by the fusion of multiple subject-specific curves,” Neurocomputing 275, 1295–1307 (2018).
A. J. Logan, G. E. Gordon, and G. Loffler, “Contributions of individual face features to face discrimination,” Vision Res. 137, 29–39 (2017).
Shilpi Singhas and S. V. Prasad, “Techniques and challenges of face recognition: A critical review,” Procedia Comput. Sci. 143, 536–543 (2018). https://doi.org/10.1016/j.procs.2018.10.427
Tanwir Khan, Computer Vision–Detecting Objects Using Haar Cascade Classifier (2019). https://towardsdatascience.com/computer-vision-detecting-objects-using-haar-cascade-classifier-4585472829a9. Accessed March 24, 2021.
K. K. Vasil’ev, V. E. Dement’ev, and N. A. Andriyanov, “Application of mixed models for solving the problem on restoring and estimating image parameters,” Pattern Recognit. Image Anal. 26 (1), 240–247 (2017). https://doi.org/10.1134/S1054661816010284
K. K. Vasiliev and N. A. Andriyanov, “Synthesis and analysis of doubly stochastic models of images,” CEUR Workshop Proc. 2017, 145–154 (2005).
Yang Zhang, Peihua Lv, and Xiaobo Lu, “A deep learning approach for face detection and location on highway,” IOP Conf. Ser.: Mater. Sci. Eng. 435, 012004 (2018). https://doi.org/10.1088/1757-899X/435/1/012004
Zetao Chen, Obadiah Lam, Adam Jacobson, and Michael Milford, “Convolutional neural network-based place recognition,” arXiv (2014). arXiv:1411.1509 [cs.CV]