Brazilian Mercosur License Plate Detection: a Deep Learning Approach Relying on Synthetic Imagery

Ribeiro, Vinícius Campos Tinoco; Greati, Vitor Rodrigues; Bezerra, Aguinaldo; Silvano, Gilles; Silva, Ivanovitch; Endo, Patrícia Takako; Lynn, Theo

doi:10.1109/sbesc49506.2019.9046091

Cited by 8 publications

(1 citation statement)

References 33 publications

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“…-Independent Variables: After the dataset creation, a distribution was made into training and test image datasets in proportion of 80% and 20% respectively, 240 images for training and 60 images for test. This approach was used by Ribeiro et al [12] and followed by this present project.…”

Section: Methodsmentioning

confidence: 99%

Uma aplicação de softwares de engenharia em processamento de imagem de tráfego: uma revisão baseada nos métodos tradicionais.

COSTA,

ARAUJO

2023

Blucher Engineering Proceedings

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The competitive industrial environment motivates automotive companies to continuously search for initiatives that disrupt problem solving and decision making, especially a better understanding of how customers use their vehicles and interacts with such technological experience and diverse use. It is impressive the amount of research related to image recognition and the application of computer vision to get unclear information related to driver intention and the environment during driving events. Nowadays, in-vehicle sensors and online city cameras facilitate almost continuous monitoring of vehicles and traffic, contributing to analytical assessments that are increasingly enhancing the studies about autonomous vehicle and smart cities. This work presents an academic application of computer vision based on engineering software in comparison with a traditional approach using Python. The public data source consists of Brazilian traffic images, and labels will provide tabular information about that environment. A classification model will be built to analyze the conduct of heavy vehicles and will be compared by both methods. Find a way to leverage support tools exploiting Machine Learning and Image Processing seems an innovative and intelligent pathway for customer-centric companies.

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Section: Methodsmentioning

confidence: 99%