International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Automatic License Plate Recognition with CNN Method in Machine Learning

Author(s) Lokesh Jain, Geetika Vashisht
Country India
Abstract In this period of consistently expanding innovation, there is a tremendous interest among individuals in a no-problem-at-all day-to-day way of life and travel. With the gigantic improvement in the vehicular area consistently, following individual cars has turned into an undeniably challenging task. With reconnaissance cameras on the side of the road, this thought proposes automatic license plate recognition for vehicles rushing. To tackle this issue, a proficient deep learning model called a Convolutional neural network is utilized for object identification and Simple OCR for character recognition. ALPR (Automatic License Plate Recognition), quite possibly one of the most broadly utilized computer vision applications is the subject of the proposed work. Furthermore, the paper provides insights into publicly accessible evaluation metrics and benchmark results, establishing a standardized framework for the quantitative assessment of automatic license plate recognition research employing CNN image resnet. The ultimate goal is to contribute to a deeper understanding of the latest state-of-the-art studies in automatic license plate recognition, particularly within the context of CNN image resnet in machine learning.
Keywords Automatic License Plate Recognition, Deep Learning, CNN., Image Processing
Field Engineering
Published In Volume 6, Issue 1, January-February 2024
Published On 2024-01-20
Cite This Automatic License Plate Recognition with CNN Method in Machine Learning - Lokesh Jain, Geetika Vashisht - IJFMR Volume 6, Issue 1, January-February 2024. DOI 10.36948/ijfmr.2024.v06i01.11930
DOI https://doi.org/10.36948/ijfmr.2024.v06i01.11930
Short DOI https://doi.org/gtfmtp
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