Deep Learning-based Face Recognition in Help of Historical Data and Event Analyses

Authors

  • Radovesta Stewart Burgas State University “Prof. Dr. Asen Zlatarov”, Burgas, Bulgaria
  • Krasimir Kralev Burgas State University “Prof. Dr. Asen Zlatarov”, Burgas, Bulgaria
  • Daniel Stoyanov Burgas State University “Prof. Dr. Asen Zlatarov”, Burgas, Bulgaria

DOI:

https://doi.org/10.55630/dipp.2025.15.10

Keywords:

Deep Learning, Face Recognition, Historical Analyses, Emotion Recognition

Abstract

This study focuses on the deep learning methods for face recognition in order to spot society patterns from historical databases. The results can enrich historical narratives by quantifying visual cues that are often overlooked in traditional archival research. Scanned photographs from the early 20th century have been used to perform recognition of the basic facial attributes – gender, age and emotion.

References

Chen, Y., Ruan, X., & Jain, R. H. (2024). Deep convolutional neural networks. In Recent advances in logo detection using machine learning paradigms. Intelligent Systems (Vol. 255). Springer. https://doi.org/10.1007/978-3-031-59811-1_1

Guo, J., & Deng, J. (2019). InsightFace: 2D and 3D face analysis project. https://github.com/deepinsight/insightface

Hernandez-Matamoros, A., Bonarini, A., Escamilla-Hernandez, E., Nakano-Miyatake, M., & Perez-Meana, H. (2015). A Facial Expression Recognition with Automatic Segmentation of Face Regions. In: Fujita, & H., Guizzi, G. (Eds.), Intelligent Software Methodologies, Tools and Techniques. SoMeT 2015. Communications in Computer and Information Science, vol 532 (pp. 529–540). Springer, Cham. https://doi.org/10.1007/978-3-319-22689-7_41

Kaur, S., & Sharma, D. (2023). Comparative study of face detection using cascaded Haar, HOG and MTCNN algorithms. In 2023 3rd International Conference on Advancement in Electronics & Communication Engineering (AECE) (pp. 536–541). IEEE. https://doi.org/10.1109/AECE59614.2023.10428242

RHM Burgas. (2022). 24th Black Sea Infantry Regiment in the Balkan wars 1912–1913. https://burgasmuseums.bg/en/encdetail/24th-black-sea-infantry-regiment-125

Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014). DeepFace: Closing the gap to human-level performance in face verification. In 2014 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1701–1708). IEEE. https://doi.org/10.1109/CVPR.2014.220

Downloads

Published

2025-09-05

How to Cite

Stewart, R., Kralev, K., & Stoyanov, D. (2025). Deep Learning-based Face Recognition in Help of Historical Data and Event Analyses. Digital Presentation and Preservation of Cultural and Scientific Heritage, 15, 107–116. https://doi.org/10.55630/dipp.2025.15.10

Issue

Vol. 15 (2025): Digital Presentation and Preservation of Cultural and Scientific Heritage

Section

Full Papers

License

Copyright (c) 2025 Digital Presentation and Preservation of Cultural and Scientific Heritage

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Most read articles by the same author(s)

1 2 > >>