Weapon Detection in Real-Time CCTV Using Deep Learning

Authors: Prof . H.R Agashe, Vipul Rajesh Darade, Animesh Kiran Buwa, Omkar Pradeep Badve, Yadnik Kiran Gaikwad

Country: India

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Abstract: Weapon detection is a critical task in ensuring public safety and security in various environments, including airports, schools, and public gatherings. In recent years, deep learning techniques have shown remarkable success in object detection tasks, prompting the development of sophisticated models tailored for detecting weapons. This paper presents a novel approach to weapon detection using the You Only Look Once (YOLO) architecture, a state-of-the-art object detection framework known for its speed and accuracy. By leveraging the YOLOv4 model’s ability to detect objects in real-time with a single pass through the network, our proposed system achieves effi cient and reliable weapon detection in diverse scenarios. We first provide an overview of the YOLOv4 architecture and its key components, including the network architecture, loss function, and training methodology. We then describe our approach to adapting YOLOv4 for weapon detection, including dataset preparation, model training, and evaluation metrics. Experimental results demonstrate the effectiveness of our approach in accurately detecting weapons while maintaining real-time performance, making it suitable for deployment in various security applications. Furthermore, we discuss potential enhancements and future directions for improving the robustness and versatility of weapon detection systems based on the YOLOv4 framework. Overall, this paper contributes to advancing the field of weapon detection using deep learning techniques, offering insights and practical guidance for researchers and practitioners in the domain of public safety and security.

Keywords: Weapon detection, Yolo algorithm, security, deep learning, public safety and security

Paper Id: 230664

Published On: 2024-05-25

Published In: Volume 12, Issue 3, May-June 2024

Cite This: Weapon Detection in Real-Time CCTV Using Deep Learning - Prof . H.R Agashe, Vipul Rajesh Darade, Animesh Kiran Buwa, Omkar Pradeep Badve, Yadnik Kiran Gaikwad - IJIRMPS Volume 12, Issue 3, May-June 2024.

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