title: Web Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ðµ Ð¿Ð¾Ð¸ÑÐºÐ° ÑÐ³Ð½Ð°Ð½Ð½ÑÑ Ð°Ð²ÑÐ¾Ð¼Ð¾Ð±Ð¸Ð»ÐµÐ¹ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Web application for the search of stolen cars based on neural networks
Creators: name: ÐÐ²Ð°Ð½Ð¾Ð², ÐÐ°Ð´Ð¸Ð¼
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ
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web-ÑÐµÑÐ²Ð¸Ñ
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neural network
method
video file
video sequence
optimizer
data set
car
state number
web service
server
database

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description: The aim of this research is to develop a web application that uses neural networks to effectively identify stolen cars. The methods used include training deep learning models using a large dataset of vehicle images, as well as related information such as license plates and vehicle characteristics. The trained models are then integrated into the web application, allowing users to provide the state license plate of the car to search for it. In the course of this work, a local website was developed that uses a neural network to search for a car by state number. This product was developed to find stolen cars faster. The potential applications of the results obtained are extensive - from law enforcement agencies to insurance companies and individual vehicle owners. Law enforcement agencies can use the web application to optimize vehicle theft investigations, increasing their overall efficiency. Individual vehicle owners can use the app as an additional security measure to protect their vehicles and promptly report any potential thefts. In the presented work, there will be an overview of various neural networks. In addition, the principle of operation of the web application and the server as a whole will be described. In addition, the ability of the system to process textual information such as license plate numbers. In conclusion, it should be noted that the development of a web application based on neural networks to search for stolen cars represents significant progress in the field of vehicle safety. The potential impact of this study extends to various sectors, offering valuable support in combating vehicle theft and improving overall public safety.