Trinetra : Weapon Detection Model

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