搜索资源列表
文字识别程序
- 目前该手写体识别系统主要分为 预处理模块: 主要包括训练数据和识别数据的读取,归一化,二值化 特征提取模块:主要包括笔划方向特征和网格密度特征,还可以根据对识别率的要求继续增加其他特征 识别(分类器)模块:主要包括SVM方法和BP神经网络的方法,其中SVM方法的识别率较高,SVM+网格密度特征, 在小字符集情况下,达到了识别率97%以上 采用OO思想编写,适合做二次开发-currently the handwriting recognition system consists of pretre
nn
- 神经网络训练,可参考相应的文章,杜达《模式分类》等
chepai
- 能对车牌定位,分割,运用神经网络训练识别
face_recognition_source
- 该程序用java结合神经网络训练的方法实现了人脸识别的功能。
Classify
- VC实现的手写体识别程序。实现手写数字给出不同的分类器识别结果,可心采用模板匹配分类器(最邻近模板匹配法)识别, Bayes分类器识别(使用二值数据的Bayes方法,最小错误概率的Bayes方法,最小风险的Bayes方法),线性函数分类法识别(Fisher算法,奖惩算法,增量校正算法,LMSE算法的识别),非线性分类法(势函数法)识别,神经网络分类法识别(包括神经网络训练,神经网络建立后输出权值,测试与比较,神经网络识别)。 运行完全正确,是学习VC实现不同分类识别方法的很好代码。
Matlab实现基于神经网络的文字/字母识别
- 程序运用于MATLAB,实现了神经网络的文字识别,目前是对英文字母,当然对汉字要难些,而且可能会不是特别准确(因为需要训练的样本多了)。
RbfSingleCharRecognition
- 径向基神经网络的字符和数字识别程序,在训练的基础上进行识别-RBF neural network and digital character recognition program, the training conducted on the basis of identification
Classification
- 模式分类。包括:训练样本设计、模板匹配分类器、Bayes分类器、线性函数分类法、非线性分类法、神经网络分类法-Pattern classification. Include: training sample design, template matching classifier, Bayes classifier, a linear function of classification, non-linear classification, neural network classificat
DigitalRec
- 手写体数字识别的VC实现 使用神经网络算法对手写体数字进行识别,训练后识别率可达90%左右。-Handwritten Digit Recognition of the VC to achieve the use of neural network algorithm for handwritten numeral recognition, training, recognition rate can reach about 90.
shibie
- 基于bp神经网络的车牌识别系统 神经网络部分训练有待提高-The design of intelligent transportation systems for applications such as electronic toll,traffic flow analysis,speed Limit and red light violation enforcement has been attracted an increasing attention from researchers.I
BPneuralnetworkbasedonthematlab
- 一个基于BP神经网络的matlab程序可以实现对几种字体0-9的数字识别这个文件训练网络的压缩包-BP neural network based on the matlab program can achieve several fonts 0-9 to identify the document number of the compressed packet network training
Recog
- 用于数字字符识别。包括对含有数字的图片进行二值化,去噪,分隔字符,归一化处理,训练神经网络并识别。-For digital character recognition. Including the number of pictures that contain binary, denoising, separation characters, normalization, and identification of training neural networks.
BP---recognize-characters
- 采用三层BP神经网络训练样本,读取训练好的网络识别字符-Three-layer BP neural network training samples, read the trained network to recognize characters
recog_ANN3
- 用于数字和字母识别的神经网络训练和识别代码-For numbers and letters identify the neural network training and the identification code
shuzishibie
- 一个简单的数字识别,运用的BP神经网络训练,gui界面-A simple digital identification, the use of the BP neural network training, gui interface
shibie
- 数字识别,包括0至9还有字母M,使用BP神经网络训练,训练精度到0.001-Digital identification
number
- 基于神经网络训练测试,能识别0-9个数字,字体可不同-Neural network training based tests can identify numbers 0-9, fonts can be different
character recognition
- CNN卷积神经网络对字符进行训练、字符识别相关代码(Printed ink jet character recognition)
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- BP神经网络matlab完整代码,包括训练代码、测试代码(BP neural network matlab complete code, including the training code, test code, the image directly into the network is trained to)
cnn
- 基于python tensorflow框架构建的卷积神经网络用来识别图像,附带训练数据集的制作代码。(The convolution neural network based on the python tensorflow framework is used to identify images with the production code of the training data set.)