Corpus ID: 11538348

Reading Car License Plates Using Deep Convolutional Neural Networks and LSTMs

@article{Li2016ReadingCL,
  title={Reading Car License Plates Using Deep Convolutional Neural Networks and LSTMs},
  author={Hui Li and Chunhua Shen},
  journal={ArXiv},
  year={2016},
  volume={abs/1601.05610}
}
  • Hui Li, Chunhua Shen
  • Published in ArXiv 2016
  • Computer Science
  • In this work, we tackle the problem of car license plate detection and recognition in natural scene images. Inspired by the success of deep neural networks (DNNs) in various vision applications, here we leverage DNNs to learn high-level features in a cascade framework, which lead to improved performance on both detection and recognition. Firstly, we train a $37$-class convolutional neural network (CNN) to detect all characters in an image, which results in a high recall, compared with… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 71 CITATIONS, ESTIMATED 95% COVERAGE

    Robust License Plate Recognition With Shared Adversarial Training Network

    VIEW 4 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    A Robust Segmentation Free License Plate Recognition Method

    VIEW 10 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Towards Human-Level License Plate Recognition

    VIEW 10 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    License Plate Recognition in Diversified Situations Using Robust L-GEM-Based RBFNN

    VIEW 5 EXCERPTS
    CITES METHODS
    HIGHLY INFLUENCED

    A New CNN-Based Method for Multi-Directional Car License Plate Detection

    VIEW 8 EXCERPTS
    CITES METHODS, RESULTS & BACKGROUND
    HIGHLY INFLUENCED

    A Robust and Real-Time Approach for License Plate Detection

    • Dan Pu, Naijie Gu, Xiaoci Zhang
    • Computer Science
    • 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
    • 2018
    VIEW 8 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    License Plate Recognition using Convolutional Neural Networks Trained on Synthetic Images

    VIEW 9 EXCERPTS
    CITES BACKGROUND & METHODS
    HIGHLY INFLUENCED

    Automatic License Plate Recognition using Deep Learning Techniques

    VIEW 4 EXCERPTS
    CITES METHODS & BACKGROUND
    HIGHLY INFLUENCED

    Toward End-to-End Car License Plate Detection and Recognition With Deep Neural Networks

    VIEW 5 EXCERPTS
    CITES BACKGROUND & METHODS

    FILTER CITATIONS BY YEAR

    2016
    2020

    CITATION STATISTICS

    • 14 Highly Influenced Citations

    • Averaged 20 Citations per year from 2017 through 2019

    • 14% Increase in citations per year in 2019 over 2018

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 54 REFERENCES

    Detection of license plate characters in natural scene with MSER and SIFT unigram classifier

    • Hao Wooi Lim, Yong Haur Tay
    • Computer Science
    • 2010 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology
    • 2010
    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Deep Features for Text Spotting

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Application-Oriented License Plate Recognition

    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    A Novel Connectionist System for Unconstrained Handwriting Recognition

    VIEW 14 EXCERPTS
    HIGHLY INFLUENTIAL

    A License Plate-Recognition Algorithm for Intelligent Transportation System Applications

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    High performance offline handwritten Chinese character recognition using GoogLeNet and directional feature maps