Using neural networks to determine traffic conditions
Автор: Sinitsyn Ivan S., Sulitsky Mikhail V., Parygin Danila S., Dzhagaev Vyacheslav A., Seryakova Valeria N.
Журнал: Сетевое научное издание «Системный анализ в науке и образовании» @journal-sanse
Статья в выпуске: 2, 2022 года.
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The article discusses the factors of the road situation that affect road safety, including weather conditions as the cause of the complication of the situation on the roads, and traffic accidents, which are the result of various negative circumstances, as well as the probable cause of new negative traffic factors. A software solution is proposed for identifying negative road factors in images from surveillance cameras using the YOLO and Mask-RCNN neural network models, followed by informing users through the bot service in the Telegram messenger.
Convolutional neural network, neural network training, dataset, traffic accidents, yolo, mask-rcnn, traffic conditions, telegram bot
Короткий адрес: https://sciup.org/14124581
IDR: 14124581
