基于深度学习的车牌识别方法及系统实现

technology has been widely used in real life.Traditional license plate recognition methodshave problems in accuracy and stability,so new methods are needed to improve andoptimize them.The purpose of this study is to explore the method of license platerecognition based on deep learning and its system implementation.By constructing alicense plate recognition system,the accuracy and stability of license plate recognition areimproved,and it contributes to the development of intelligent transportation system.Thispaper first introduces the deep learning technology and its application in imagerecognition,including convolutional neural network(CNN).Then,based on thesetechnologies,a framework design of license plate recognition system is proposed,includinglicense plate location,character segmentation,character recognition and other steps.Subsequently,the accuracy and stability of the method are verified by experiments andresults analysis of real license plate images taken in a certain area.The experimental resultsshow that the license plate recognition system based on deep learning can effectivelyimprove the accuracy and stability of license plate recognition.The method is notinterfered by light,angle and other factors,and can realize the rapid recognition ofdifferent vehicles,which has a wide range of application prospects.In short,this paperproposes a method and system implementation of license plate recognition based on deeplearning,which has high accuracy and stability.With the continuous development ofintelligent transportation system,this research has great application value and developmentprospects.In the future,we can consider further optimization and improvement of thismethod,so as to better serve the needs of society and the people.This article useslightweight CNN to achieve license plate recognition.Keyword Deep learning;license plate recognition;system implementationlightweightcnn目录题目：基于深度学习的车牌识别方法及系统实现............