Deep Learning for License Plate Number Recognition: A Survey

With the continuous development of deep learning technology, object detection has become an important research direction in this field. The purpose of this study is to review the deep learning techniques and typical deep networks for license plate number detection and recognition in recent years, including CNN, RNN, GAN, Transformer, and Diffusion Model. Furthermore, we compare the advantages and disadvantages of these methods. Finally, some challenges and future development directions of deep learning technology in license plate number detection and recognition are pointed out.

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Publication Details

Published
2024-11-08
DOI
https://doi.org/10.1109/iccsi62669.2024.10799401
Citations
1
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
0.32
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article

Deep Learning for License Plate Number Recognition: A Survey

Zhuoqun Fu
1 citations
Vehicle License Plate Recognition
0.32
article

Deep Learning for License Plate Number Recognition: A Survey

Zhuoqun Fu
article en
1 citations

Abstract

With the continuous development of deep learning technology, object detection has become an important research direction in this field. The purpose of this study is to review the deep learning techniques and typical deep networks for license plate number detection and recognition in recent years, including CNN, RNN, GAN, Transformer, and Diffusion Model. Furthermore, we compare the advantages and disadvantages of these methods. Finally, some challenges and future development directions of deep learning technology in license plate number detection and recognition are pointed out.

Northwestern Polytechnical University (CN)
Openalex Percentile: Top 34%
Vehicle License Plate Recognition
0.32
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