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https://doi.org/10.17223/19988605/68/9
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Cite Publication Date: Jan 1, 2024 |
The problem of using neural network algorithms to detect a person in a video sequence in a mine is considered. Convolutional neural networks are analyzed: Faster R-CNN, YOLOv5 and YOLOv8 with n, m, x (Nano, Medium and Extra Large) and SSG assemblies for detecting objects in video with classes: miner, face, head with a helmet, helmet.
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