Machine Learning Techniques for Real-Time Human Face Recognition
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-6984-5_7
Reference25 articles.
1. Zhou, S., & Xiao, S. (2018). 3D face recognition: A survey. Human-Centric Computing Information Sciences, 8(1). https://doi.org/10.1186/s13673-018-0157-2
2. Kak, S. F., Mustafa, F. M. & Valente, P. (2018). A review of person recognition based on face model. Eurasian Journal of Science & Engineering. EAJSE2018. https://doi.org/10.23918/eajsev4i1sip157
3. Canedo, D., & Neves, A. J. (2019). Facial expression recognition using computer vision: A systematic review. MDPI. https://doi.org/10.3390/app9214678
4. Zhu, Z., & Cheng, Y. (2020). Application of attitude tracking algorithm for face recognition based on OpenCV in the intelligent door lock. Computer Communications, 154(900), 390–397. https://doi.org/10.1016/j.comcom.2020.02.003
5. Kavita, K., & Chhillar, R. S. (2022). Human face recognition and age estimation with machine learning: A critical review and future perspective. International Journal of Electrical and Computer Engineering Systems (IJECES), 13(10), 945–952. https://doi.org/10.32985/ijeces.13.10.9
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