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DesignandImplementation
- 本文论述并设计实现了一个脱机自由手写体数字识别系统。文中首先对待识别数字的预处理进行了介绍,包括二值化、平滑滤波、规范化、细化等图像处理方法;其次,探讨了如何提取数字字符的结构特征和笔划特征,并详细地描述了知识库的构造方法;最后采用了以知识库为基础的模板匹配识别方法,并以MATLAB作为编程工具实现了具有友好的图形用户界面的自由手写体数字识别系统。实验结果表明,本方法具有较高的识别率,并具有较好的抗噪性能。-This paper describes and designs a free hand
number-recognizing
- 本程序利用模板匹配实现手写体数字识别,可以作为新的模板匹配数字识别算法的基础。-The program uses the template matching handwritten numeral recognition, can be used as the basis of new template matching numeral recognition algorithm.
finalWork
- 用WEKA实现手写体数字识别,这是自己编写的,如果有错误请多多包涵-WEKA achieve handwritten digit recognition, which I have written, if there is an error, please forgive me
FeatureSubsetSelection
- 基于BP神经网络的手写体数字识别中用到的特征提取工具。-Extraction tool based on the characteristics used in the BP neural network handwritten digit recognition.
recognize
- 采用C++语言编写的基于BP神经网络的手写体数字识别程序,使用方式为通过命令提示符向main函数传递待识别的图像的绝对路径。-Using C++ language through the command prompt is passed to the main function to be identified image handwritten digit recognition based on BP neural network program, use absolute paths.
chapter14
- 利用计算机自动识别字符的技术,是模式识别应用的一个重要领域。人们在生产和生活中,要处理大量的文字、报表和文本。为了减轻人们的劳动,提高处理效率,50年代开始探讨一般文字识别方法,并研制出光学字符识别器。60年代出现了采用磁性墨水和特殊字体的实用机器。60年代后期,出现了多种字体和手写体文字识别机,其识别精度和机器性能都基本上能满足要求。如用于信函分拣的手写体数字识别机和印刷体英文数字识别机。70年代主要研究文字识别的基本理论和研制高性能的文字识别机,并着重于汉字识别的研究。-The use of
Database-digit-handwritten
- 手写体数字识别的训练数据库(MNIST)。 收集了500多位实验者的共60000个样本。-THE MNIST DATABASE of handwritten digits Four files are available on this site: train-images-idx3-ubyte.gz: training set images (9912422 bytes) train-labels-idx1-ubyte.gz: training set label
Digits-Recgnition-Based-on-SVM
- 介绍了基于SVM的手写体数字识别,是一篇不错的期刊文章-To introduce handwritten digit recognition based on SVM is a good journal articles
Handwritten_recognition_system
- Visual C++数字图像模式识别典型案例:手写体数字识别系统-Visual C++ digital image pattern recognition typical case: handwritten digital recognition system
20130413
- 基于神经网络的脱机手写体数字识别的代码,能运行-Based on the offline handwritten digital identification code of the neural network, able to run
NumberHandwritting
- 基于神经网络的手写体数字识别,它是用matlab实现的,其中用3种不同的神经的网络方法实现了手写体数字的识别,非常利于初学者的学习和交流。-Handwritten digit recognition based on neural networks, which is achieved using matlab, in which three different neural network to achieve the recognition of handwritten digits, is
gailvwangluoduishouxietideshibie
- 基于概率神经网络的手写体数字识别,可以尝试作文字图像的辨识- the programm of neural network
mnistAll
- mnistAll数据库,手写体数字识别数据库。里面有分好的训练与测试样本集及对应标签-mnistAll databases, handwritten digit recognition database. There are good training and testing sample sets and the corresponding label
numberRecognise-multi
- 采用c#开发的手写体数字识别-多样本版.rar-Digital Identification- diverse edition rar.
HDR-Using-NN
- 基于神经网络的手写体数字识别,依靠凸点特征、端点特征、二连点特征。-Handwritten Digit Recognition Using Neural Networks
hand
- 手写体数字识别开发平台是一个C++源程序代码,集中了图像处理领域绝大部分函数-Handwritten numeral recognition is an C++ development platform source code, most of the focus areas of the image processing function
chapter9
- Visual C++数字图像模式识别典型案例配套光盘 chapter9 手写体数字识别系统-ch9 ok
DigitIdent
- 要求给定数字模式样本(7X9点阵,0-9共10个数字),设计一BP神经网络进行手写体数字识别。 网络只有一个隐含层,训练样本100个,测试样本300个 -Requirements for a given sample in digital mode (7X9 lattice, a total of 10 figures 0-9), design a BP neural network to recognize handwritten digits. Network has only on
Snake
- 要求给定数字模式样本(7X9点阵,0-9共10个数字),设计一BP神经网络进行手写体数字识别。 网络只有一个隐含层,训练样本100个,测试样本300个 -Requirements for a given sample in digital mode (7X9 lattice, a total of 10 figures 0-9), design a BP neural network to recognize handwritten digits. Network has only on
Code
- 基于概率神经网络的手写体数字识别,人工智能方面的应用-Handwritten numeral recognition based on probabilistic neural networks, artificial intelligence applications