许可证
卷积神经网络
计算机科学
人工智能
字符识别
深度学习
光学字符识别
模式识别(心理学)
人工神经网络
特征提取
新认知
集合(抽象数据类型)
性格(数学)
语音识别
图像(数学)
数学
程序设计语言
操作系统
几何学
作者
Bianlian Zhang,Chaohua Liu,Xiaoli Zhang
摘要
This paper is based on the deep learning license plate recognition system, which is a method of deep learning in the recognition of license plates.In the recognition of license plates, improved Convolutional-Neural-Network (CNN) is used to identify the accuracy and speed of recognition. The experimental results show that the application of convolutional neural network in license plate recognition can effectively improve the recognition rate of the license plate in various environments such as pollution, insufficient illumination, etc. This recognition rate is improved by means of a large training character set. The more character forms included in the character set, the higher the recognition rate, the more the license plate character recognition rate can reach 98% or more. In addition, for the trained convolutional neural network, including the license plate extraction and pre-processing recognition speed can also reach less than 30 ms.
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