Face Recognition Using Machine Learning: Techniques, Methods and Future Challenges
DOI:
https://doi.org/10.26692/surj-ss.v56i02.7463Keywords:
Face Recognition, Machine Learning, ML, Partial Differential Equation, PDE and Biharmonic EquationAbstract
Privacy and security becomes the global challenge and security of authentication is most prior for users, technologists, and researchers. So, facial recognition is the problem of authentication systems, and breaching cases are reported. Thus, Facial recognition attracted the researcher’s attention and grew as an interesting and challenging theme in various domains such as computer vision, machine learning, and digital image processing. Moreover, it covers a huge number of applications such as personnel sign systems, search engines, and prisoner detecting systems. In this paper, the discrete quantity of Biharmonic Equation (PDE) is proposed for a 3D image in which a gray level matrix represents the image and compares the origin face image with a constructed image. In this regard, some functions are also defined and designed by the Biharmonic Equation; these functions represent the parametric curve equations in space and divide the surface.
References
Abdi, F., Ahmadi, M., & Ghanem, M. (2023). AM-IF: Adaptive Multi-Path Interest Forwarding in named data networking. Future Generation Computer Systems, 148, 564–583.
Ayeswarya, S., & Singh, K. J. (2024). A comprehensive review on secure biometric-based continuous authentication and user profiling. IEEE Access.
Bellamy, R., & Kröger, S. (2024). Truthfulness, pluralism and the ethics of democratic representation. The British Journal of Politics and International Relations, 13691481241287184.
Dash, P., Sarma, M., & Samanta, D. (2024). Privacy preserving unique identity generation from multimodal biometric data for privacy and security applications. Security and Privacy, 7(3), e375.
Despotović, A., Parmaković, A., & Miljković, M. (2023). Cybercrime and cyber security in fintech. In Digital transformation of the financial industry: approaches and applications (pp. 255–272). Springer.
Duan, H., & Wang, G. (2023). Partial differential grey model based on control matrix and its application in short-term traffic flow prediction. Applied Mathematical Modelling, 116, 763–785.
Hildreth, W., Fierstein, J., & Vazquez, J. (2023). Ages of the granitic basement of Long Valley Caldera, California, USA, and siting of the Quaternary granite-rhyolite pluton. Bulletin, 135(11–12), 2753–2766.
Huang, B., Wang, Z., Wang, G., Han, Z., & Jiang, K. (2023). Local eyebrow feature attention network for masked face recognition. ACM Transactions on Multimedia Computing, Communications and Applications, 19(3), 1–19.
Islam, M. M., Nooruddin, S., Karray, F., & Muhammad, G. (2023). Multi-level feature fusion for multimodal human activity recognition in Internet of Healthcare Things. Information Fusion, 94, 17–31.
Khan, H. U., Sohail, M., Nazir, S., Hussain, T., Shah, B., & Ali, F. (2023). Role of authentication factors in Fin-tech mobile transaction security. Journal of Big Data, 10(1), 138.
Lattas, A., Moschoglou, S., Ploumpis, S., Gecer, B., Deng, J., & Zafeiriou, S. (2023). Fitme: Deep photorealistic 3d morphable model avatars. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 8629–8640.
Memon, S., Manivannan, N., Noor, A., & Tigli, C. (2011). Security Issues in Automated Fingerprint Identification Systems. Bahria University Journal of Information & Communication Technologies, 4(1), 9–14.
Prakash, A. J., Patro, K. K., Samantray, S., Pławiak, P., & Hammad, M. (2023). A deep learning technique for biometric authentication using ECG beat template matching. Information, 14(2), 65.
Suchde, P., Jacquemin, T., & Davydov, O. (2023). Point cloud generation for meshfree methods: An overview. Archives of Computational Methods in Engineering, 30(2), 889–915.
Wang, Z., Ma, F., Ji, P., & Fu, C. (2024). Image Denoising Based on an Improved Wavelet Threshold and Total Variation Model. International Conference on Intelligent Computing, 142–154.
Zhang, J., Luximon, Y., Shah, P., & Li, P. (2023). 3D statistical head modeling for face/head-related product design: a state-of-the-art review. Computer-Aided Design, 159, 103483.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
