A review of face recognition technology based on deep learning

Zexu Gao

doi:10.1117/12.3026519

27 March 2024 A review of face recognition technology based on deep learning

Zexu Gao

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 1310530 (2024) https://doi.org/10.1117/12.3026519
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

Face recognition technology is a kind of biometric recognition technology that has developed rapidly in recent years, and the method based on deep learning is one of the most promising research directions. In this paper, the face recognition technology based on deep learning is reviewed and analyzed. Firstly, the mainstream data sets of face recognition technology are introduced. Then, two kinds of face recognition methods based on large-scale data and synthetic data are analyzed and verified by experiments. Finally, the advantages and challenges of the face recognition method based on deep learning are discussed, and some hot spots and future development directions in current research are prospected. However, face recognition technology based on deep learning has higher accuracy and robustness. At the same time, there are still problems such as unbalanced data sets, responses in complex scenarios, and data privacy protection. This paper provides important reference and guidance for researchers by systematically combing and summarizing the research progress and application in this field and then promotes the development and application of face recognition technology.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zexu Gao "A review of face recognition technology based on deep learning", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 1310530 (27 March 2024); https://doi.org/10.1117/12.3026519

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KEYWORDS

Facial recognition systems

Deep learning

Data modeling

Education and training

3D modeling

Feature extraction

Image processing

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