Digital Intelligence for Global Good
Articles

Trinetra : Weapon Detection Model

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  • Jayanta Chowdhury
Jayanta Chowdhury
Swami Vivekananda University

Published 2025-12-22

Keywords

  • Weapon Detection,
  • YOLOv4,
  • Deep Learning,
  • Object Detection,
  • Security,
  • Surveillance,
  • Computer Vision,
  • Machine Learning
    • ...More
    Less

How to Cite

Chowdhury, Jayanta. “Trinetra : Weapon Detection Model”. Swami Vivekananda University Press, Dec. 2025, pp. 31-37, https://swamivivekanandauniversitypress.com/index.php/svup/article/view/209.

Copyright (c) 2025 Swami Vivekananda University Press

Creative Commons License

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

Abstract

Ensuring public safety through efficient weapon detection is a critical challenge in modern security systems. Traditional methods often fail to detect weapons in real-time, limiting their effectiveness. This paper presents an advanced approach to weapon detection using the YOLOv4, deep learning model. The research explores the architecture of YOLOv4 and introduces modifications to enhance weapon detection accuracy. The proposed model undergoes extensive testing in diverse environments, demonstrating its robustness, efficiency, and superiority over conventional methods. The results indicate significant improvements in real-time weapon identification, making YOLOv4 a promising tool for security applications.

DOI - https://doi.org/10.65525/SVUP.9788199565463.2026.31-37

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