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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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AI Based Vehicle Information and Fraudulent Detection System

Authors: Mayur Mundankar; Vedant Mute; Krushna Gomsale; Prof. V. B. Baru; Mr. T. S. Wakde;

AI Based Vehicle Information and Fraudulent Detection System

Abstract

The proposed system uses AI model for number plate detection. It uses computer vision and machine learning. The system checks the vehicle number plates in real time using Raspberry pi, a camera, Open CV, OCR (Optical Character Recognition) and YOLO model. This system uses a Raspberry Pi, a camera, OpenCV, OCR, and the YOLO model. These tools work together to examine car number plates in real-time. The system can automatically identify car registration details from photos and videos. This capability is particularly useful for Regional Transport Office work and helps to prevent fraud. The technology uses artificial intelligence to catch fake activities, like stolen or fake license plates, with high accuracy. The goal is to offer a solution that can grow in size and is low-cost for real-world use. This research aims to boost automated law enforcement and smart traffic monitoring.

Keywords

License plate recognition, machine learning, computer vision, OpenCV, optical character recognition (OCR), Object detection, Automation.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green