Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)

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Research on Facial Recognition of Drones Based on YOLO Visual Model

Authors
Shuai Fang1, *, Yunong Li2, Hanshuo Zhang3
1Detroit Green Technology Institute, Hubei University of Technology, Wuhan, 430000, China
2Institute of Intelligent Engineering, Shenyang City University, Shenyang, 110000, China
3Suzhou Science & Technology, Town Foreign Language High School, Suzhou, 215000, China
*Corresponding author. Email: a900082@correo.umm.edu.mx
Corresponding Author
Shuai Fang
Available Online 31 August 2025.
DOI
10.2991/978-94-6463-821-9_87How to use a DOI?
Keywords
YOLOV8S; Face Recognition; Drones
Abstract

In today’s society, with the vigorous development of various undertakings, drones have been widely applied in numerous industry fields. This trend has driven the rapid evolution of drone systems to adapt to diverse application scenarios. However, existing technologies and systems have some minor issues that need to be addressed. By introducing advanced facial recognition technology, we aim to endow related devices with the ability to accurately identify, interpret and execute instructions, thereby effectively liberating labor. Therefore, based on the YOLOv8s visual model and using the WIDERFACE dataset as the training set, we have developed a system composed of four parts: data input layer, feature extraction backbone, feature fusion neck, and detection output head. In the feature extraction backbone part, we have conducted research on facial recognition and applied it to drones. Through relevant research, the experimental results show that the model still demonstrates excellent facial recognition capabilities in various backgrounds and complex lighting conditions, achieving high accuracy levels in many scenarios.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
Series
Advances in Engineering Research
Publication Date
31 August 2025
ISBN
978-94-6463-821-9
ISSN
2352-5401
DOI
10.2991/978-94-6463-821-9_87How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Shuai Fang
AU  - Yunong Li
AU  - Hanshuo Zhang
PY  - 2025
DA  - 2025/08/31
TI  - Research on Facial Recognition of Drones Based on YOLO Visual Model
BT  - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
PB  - Atlantis Press
SP  - 908
EP  - 918
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-821-9_87
DO  - 10.2991/978-94-6463-821-9_87
ID  - Fang2025
ER  -