Detection of armed people in a video stream using convolutional neural networks

Abstract

Information technology for detecting armed people is proposed and its software implementation is investigated. The YOLO convolution neural network was used to detect objects in real time. The Python programming language and the PyTorch library were used to develop the neural network. A program designed to detect armed people in a video stream has been created, the functionality of which allows classifying the type of recognized weapon.