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林健写的Matlab在图像处理与目标识别方面的应用实验，包括染色体识别与统计、汽车牌照定位与字符识别、基于BP神经网络识别字符的简单实验。-Lam Kin Writing at the Matlab image processing and target recognition application experiments, including chromosome identification and statistics, vehicle license positioning and c
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《数字图像处理与机器视觉:Visual C++与Matlab实现》4
特征提取,图像识别初步,人工神经网络,基于ANN的数字字符识别系统-" Digital image processing and machine vision: Visual C++ and Matlab to achieve" four feature extraction, image recognition initially, artificial neural network, ANN base
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一个关于车牌识别的完整程序，字符识别部分用的是神经网络的相关知识-A complete program of license plate recognition, character recognition part of the neural network with the knowledge
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基于matlab的车牌识别软件，能够对车牌进行准确的定位与识别，可以运行。字符识别采用BP神经网络的方法。-Accurate positioning and recognition based on the Matlab license plate recognition software, the license plate, you can run. Character recognition using the method of BP neural network.
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车牌识别系统 实现车牌识别，包括定位、分割和字符识别，识别方法是神经网络-License plate recognition system to achieve recognition, including positioning, segmentation and character recognition, neural network identification method is
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matlab 车牌识别，含有gui界面，边缘检测车牌定位，神经网络字符识别(Matlab license plate recognition, including GUI interface, edge detection, license plate location, neural network, character recognition)
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BP神经网络基本原理概述：这种网络模型利用误差反向传播训练算法模型，能够很好地解决多层网络中隐含层神经元连接权值系数的学习问题，它的特点是信号前向传播、误差反向传播，简称BP（Back Propagation）神经网络。BP学习算法的基本原理是梯度最快下降法，即通过调整权值使网络总误差最小，在信号前向传播阶段，输入信号经输入层处理再经隐含层处理最后传向输出层处理；在误差反向传播阶段，将输出层输出的信号值与期望输出信号值比较得到误差，若误差较大则把误差信号传回隐含层直至输入层，在各层神经元中使用
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基于BP人工神经网络的数字字符识别及MATLAB实现。(Digital character recognition and MATLAB implementation based on BP artificial neural network.)
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