Weapon Detection Using Deep Learning: HLD and LLD Documentation

This paper presents a comprehensive study and implementation of a deep learning–based weapon detection system using state-of-the-art convolutional neural network (CNN) architectures and object detection algorithms such as SSD-MobileNet, Faster R-CNN, and YOLO. The system aims to identify and locate weapons in real-time video streams with high accuracy and speed. The methodology includes dataset preparation, model training, architecture design, and performance evaluation based on metrics such as precision, mean average precision (MAP), and F1 score.