Vehicle Number Plate Recognition Using Adaptive Adaptive Recurrent Neural Network

被引：0
|
作者：
Lakshmmi, Aishwarya R. [1 ]
Kavya, M. [1 ]
Shree, Jai M. [1 ]
Maheswari, B. [1 ]
Dharshani, U. [1 ]
机构：
[1] Ayya Nadar Janaki Anim Coll Virudhunagar, Dept Comp Sci, Sivakasi, India
来源：
2024 5TH INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN INFORMATION TECHNOLOGY, ICITIIT 2024 | 2024年
关键词：
Adaptive Recurrent Neural Network; Vehicle Number Plate Recognition (VNPR); Long Short-Term Memory (LSTM); Optical Character Recognition (OCR) and Image Processing;
D O I：
10.1109/CITIIT61487.2024.10580272
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Vehicle number plate recognition (VNPR) is a critical component in various transportation and security applications. This paper presents a novel approach to VNPR leveraging Adaptive Recurrent Neural Networks (ARNNs). Our method employs an ARNN architecture designed to process sequential data, allowing for efficient extraction of features from license plate images. We utilize a dataset consisting of labeled vehicle images for training and evaluation. Through extensive experimentation, we demonstrate the effectiveness of our approach, achieving high accuracy in license plate recognition tasks. Our results highlight the potential of ARNN-based methods in the field of VNPR, paving the way for improved automation and efficiency in transportation systems and law enforcement.
引用
收藏
页数：5
相关论文
共 50 条
  • [21] Using recurrent neural network for adaptive predistortion linearization of RF amplifiers
    Li, CG
    He, SB
    Liao, XF
    Yu, JB
    INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, 2002, 12 (01) : 125 - 130
  • [22] BP-Neural Network for Plate Number Recognition
    Wang, Jia
    Yan, Wei Qi
    INTERNATIONAL JOURNAL OF DIGITAL CRIME AND FORENSICS, 2016, 8 (03) : 34 - 45
  • [23] Vehicle License Plate Localization and License Number Recognition Using Unit-Linking Pulse Coupled Neural Network
    Zhao, Ya
    Gu, Xiaodong
    NEURAL INFORMATION PROCESSING, ICONIP 2012, PT V, 2012, 7667 : 100 - 108
  • [24] An Implementation of Number Plate Recognition without Segmentation using Convolutional Neural Network
    Liu, Jie
    Li, Xin
    Zhang, Hao
    Liu, Chengcheng
    Dou, Lei
    Ju, Lei
    2017 19TH IEEE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS (HPCC) / 2017 15TH IEEE INTERNATIONAL CONFERENCE ON SMART CITY (SMARTCITY) / 2017 3RD IEEE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND SYSTEMS (DSS), 2017, : 246 - 253
  • [25] Image recognition using adaptive fuzzy neural network and wavelet transform
    Zeng, HL
    Yi, Y
    ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING, 2003, 2639 : 635 - 639
  • [26] Number Recognition of Parts Book Schematics using Convolutional Recurrent Neural Network
    Genc, Erdal
    Shin, Hee Ran
    Park, Jang Sik
    2018 18TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2018, : 1190 - 1192
  • [27] Improved bilateral neural network adaptive controller using neural network and adaptive method
    Li, Yafei
    Li, Yixin
    Sun, Xiaohui
    Zheng, Wenfeng
    Yin, Lirong
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2020, 127 : 50 - 51
  • [28] Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network
    Tang, Chen
    Chen, Jianyu
    Tomizuka, Masayoshi
    2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2019, : 3846 - 3852
  • [29] A recurrent fuzzy neural network for adaptive speech prediction
    Stavrakoudis, D. G.
    Theocharis, J. B.
    2007 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-8, 2007, : 3640 - 3645
  • [30] A recurrent neural network for adaptive beamforming and array correction
    Che, Hangjun
    Li, Chuandong
    He, Xing
    Huang, Tingwen
    NEURAL NETWORKS, 2016, 80 : 110 - 117
12345