Close-Combat Weapon Detection in Crisis Zones using YOLOv8
Keywords:
Object Detection, YOLOv8, Crisis-Affected Regions, Cameroon Security, SurveillanceSynopsis
This is a Chapter in:
Book:
Intelligent and Sustainable Solutions
Print ISBN 978-1-6692-0012-3
Online ISBN 978-1-6692-0011-6
Series:
Chronicle of Computing
Chapter Abstract:
Enhancing security measures in the crisis-affected regions of Cameroon, which have faced prolonged unrest over the years, is critically important. Detecting close-combat weapon within dense crowds can significantly improve surveillance and safety amidst ongoing challenges. These regions require advanced security solutions to address persistent threats faced by the local population. This study develops a detection model based on the You Only Look Once (YOLOv8) architecture to accurately identify and segment sticks and machetes in these crisis-affected areas. By assembling a diverse dataset that captures various scenarios, orientations, and lighting conditions, the model learns to recognize the distinctive features of these objects. By enhancing security measures through advanced technology, this study aims to contribute to ongoing efforts to safeguard communities and restore stability in these troubled areas.
About this Paper
Cite this paper as:
Nkamgan L., Onanena Guelan R., Mbous Ikong J., Videme Bossou O., Essimbi Zobo B.(2025) Close-Combat Weapon Detection in Crisis Zones using YOLOv8. In: Tiako P.F. (ed) Intelligent and Sustainable Solutions. Chronicle of Computing. OkIP. CAIF25#10. https://doi.org/10.55432/978-1-6692-0011-6_7
Presented at:
The 2025 OkIP International Conference on Artificial Intelligence Frontiers (CAIF) in Oklahoma City, Oklahoma, USA, and Online, on April 2, 2025
Contact:
Laurent Nkamgan
nkamgans@gmail.com
References
Yan, W; Kehua, Z.; Ling, W; Lintong, W. Improved YOLOv8 Algorithm for Rail Surface Defect Detection, in IEEE Access, vol. 12, pp. 44984- 44997, 2024.
Lou, H.; Duan, X.; Guo, J.; Liu, H.; Gu, J.; Bi, L.; Chen, H. DCYOLOv8: Small-Size Object Detection Algorithm Based on Camera Sensor. Electronics 2023, 12, 2323.
Narejo, S.; Pandey, B.; Esenarro, V.; Rodriguez, C.; Anjum, M. Weapon Detection Using YOLO V3 for Smart Surveillance System. Mathematical Problems in Engineering. 2021. 1-9. 10.1155/2021/9975700.
Jamilu, S.; Majeed, H. Weapon Detection for Smart Surveillance System using YOLOV6. Global Journal of Research in Humanities and Cultural Studies ISSN: 2583-2670 (Online) Volume 02— Issue 05 — Sept.-Oct. 2022
Liyao, L. Improved YOLOv8 Detection Algorithm in X-ray Contraband. Advances in Artificial Intelligence and Machine Learning. 2023:3(3):72.
Armstrong, A.; Bin, W.; Ulas, B.; Yaw, A. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, BC, Canada,2023, pp.5350-5358, Doi: 10.1109/CVPRW59228.2023.00564.
Motwani, N.; Soumya, S. Human Activities Detection using Deep Learning Technique- YOLOv8. ITM Web of Conferences. 56. 10.1051/itmconf/ 20235603003.
