搜索资源列表
TrackStructure
- 手写体数字识别系统 可执行 c++ 输入图像应为bmp格式图片 可以在画图中手写数字然后保存放入程序中即可-c++
shouxietisuzishibie
- 用matlab实现的基于概率神经网络的手写体数字识别程序,这是一个概率神经网络的实际应用-Using matlab to achieve based on probabilistic neural network handwritten numeral recognition program, which is the practical application of a probabilistic neural network
gL
- 《MATLAB神经网络原理与实例精解》中chap13的例子 基于概率神经网络的手写体数字识别-" MATLAB network principles and examples of fine nerve Solutions" in the example chap13- Based Probabilistic Neural Network handwritten numeral recognition
handwritten-numeral-recognition
- 本案例描述了图像中手写阿拉伯数字的识别过程,对手写数字识别的基于统计的方法进行简要介绍和分析,并通过开发一个小型的手写体数字识别系统来进行实验。手写体数字识别系统需要实现手写数字图像的读取功能、特征提取功能、数字的模板特征库的建立功能及识别功能-This case describes the image recognition process handwritten Arabic numerals, a brief descr ipti
TestCopybookDetect
- 基于深度学习的手写体汉字识别,所用框架为Mxnet框架-Handwritten Chinese character recognition
hard_nodyd
- 手写体汉字识别源码,网上流行很广泛的,有兴趣的来-Online handwritten Chinese character recognition source code, a wide range of popular, are interested in
kuaisushouxietishuzizifushibie
- 通过模拟人眼识别数字字符的过程,提出了一种基于字符整体特征的快速手写体数字字符识别方法。此方法不需要对字符图像做复杂的细化处理,减少了细化形变可能带来的误识和拒识,也不需要进行复杂的笔道特征分析,因此速度很快。同时,由于不同人书写的数字字符的整体特征都相同,因此此方法的识别率也非常高。-n this paper, a fast handwritten digital character recognition method based
ML_project
- 程序是对手写体数字进行识别,用knn算法,代码编写是用java。训练样本和验证样本都在代码中提供了。-The program is to handwriting figures to identify, with knn algorithm, the code is written with java. Training samples and validation samples are provided in the code.
Handwriten
- 用java编写的手写体数字识别,采用knn方法,识别的训练和测试对象来自mnist数据库的数据,已经将解压后文件放进去了,算法包括文件的读取,测试部分还有识别算法。 -Written by java handwriting digital recognition, using knn method to identify the training and test objects the mnist data, has been e
BPandBayeserandzjl
- 手写体数字识别的程序,用了三种方法,贝叶斯,最近邻和BP神经网络,用MATLAB编写的,算法简单易懂,结构清晰-Handwritten digital recognition procedures, using three methods, Bayesian, Nearest Neighbor and BP neural network, written in MATLAB, the algorithm is easy to under
shouxiehanzijiegou
- 针对手写体汉字识别问题,选取笔段和笔划作为基元,分析手写体汉字的组成规律和变形规律,提出了两种汉字结构模型:笔段中心点模型和笔划关系矩阵模型,以及基于模型的分类依据和识别方法。根据所提出的模型,采用两级分类方案构造汉字识别系统 粗分类采用笔段中心点法,细分类采用笔划关系矩阵法。-Aiming at the problem of handwritten Chinese character recognition, selecting pe
Science-2015-Lake-1332-8
- 这是一篇用小数据学习来识别手写体字母的论文,作者是MIT的博士。(One-shot learning paper of handwritten character recognition.)
OCR
- OCR 数字识别 自由手写体 离线 matlab平台 识别0-9的数字(OCR digital recognition free handwritten off-line matlab platform to identify 0-9 numbers)
simpleOCR
- OCR 数字识别 大写字母识别 自由手写体数字识别 离线 matlab平台 模式识别 识别数字0-9 识别大写字母(OCR digital recognition free handwritten off-line matlab platform to identify 0-9 numbers)
machine learning
- 反向传播算法与利用卷积神经网络识别手写体(Back propagation algorithm and recognition of handwriting by using convolution neural network)
Run_MNIST
- 下载MNIST数据集(手写体数字0-9)后,搭建卷积神经网络,将输入的数据集经过一层一层的卷积,到最后计算交叉熵,用梯度下降算法去优化它,使它变得最小,这就训练出了权重和偏置量,识别的准确率为91%(Download the MNIST data set (handwritten number 0-9), build a convolutional neural network, the input data set by convol
DeepLearnToolbox-master
- CNN,DBN算法可以对手写体数字进行识别,准确率高(CNN and DBN algorithm can recognize handwritten numerals with high accuracy)