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

O. K. Kolesnytsky, E. V. Yankovsky, I. K. Denisov, I. R. Arsenyuk
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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.
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利用卷积神经网络检测视频流中的武装人员
提出了探测武装人员的信息技术,并对其软件实现进行了研究。使用 YOLO 卷积神经网络实时检测物体。神经网络的开发使用了 Python 编程语言和 PyTorch 库。创建了一个用于检测视频流中携带武器者的程序,其功能可对识别出的武器类型进行分类。
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