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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
digits
- 手写体二进制图片库,用于机器学习的训练集和测试集。-Handwriting binary image gallery, used for training set and testing set of machine learning.
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
tiny-dnn-master
- cnn卷积神经网络实现mnist的手写体识别程序-CNN convolution neural network to realize mnist handwritten recognition program
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 iption and analysis of the handwri
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
Hinton
- Hinton手写体识别实验代码,原始代码+部分中文注释。-Hinton scr ipt code identification experiment
deep-learning-reconstruction
- 深度学习 手写体识别学习的例子,请大家批评指正-deep learning reconstruction
11
- 手写体识别_模板匹配识别方法,通过matlab实现基于神经网络的手写数字识别-Handwriting recognition _ template matching method, the matlab implementation of handwritten digit recognition based on Neural Network
Handwriting-recognition-algorithm
- 基于卷积神经网络的手写体识别算法,测试数据和训练数据都有,笨人已经检验过,很好用-Handwriting recognition algorithm based on the convolution neural network
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 on the overall character of ch
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 understand, clear structure
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 pen and stroke as primitives, an
shuangtanxingwangluo
- 特征提取是手写体汉字识别的关键,目前四方向网格特征已被实验证实是一种较好的手写体汉字特征。 针对通常的纵横弹性网格对汉字“撇、捺”笔画特征提取的不足.提出一种新的网格构造技术——对角弹性网格,它由45度和135度的对角直线构成,将汉字图像划分为多个菱形,能够很好地适应汉字在“撇、捺”方向的变化。将这两种网格单独,以及相互组合成双网格等情况分别进行手写体识别实验,实验结果验证了对角弹性网格的有效性和双弹性网格的高识别率性。 -Feature extraction is the key to
基于概率神经网络的手写体数字识别
- 基于概率神经网络的手写数字识别,利用概率神经网络识别1-9的手写数字,matlab程序(Handwritten numeral recognition based on probabilistic neural network)
CNN-master
- 深度学习 卷积神经网络 手写体识别 准确率98%(deeplearning CNN handwrite accuracy98%)
MNIST
- MNIST手写体数字识别库及图片提取代码MNIST手写数字库识别实现摘要手写数字识别是模式识别的应用之一。文中介绍了手写数字的一些主要特征,并提出了截断次数特征并利用截断次数特征进行了实验(MNIST handwritten digital identification library and picture extraction code MNIST handwritten numeral library identification implementation summary Handwr
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.)
handwriting recognition GUI
- 本文主要实现手写数字识别,利用多类逻辑回归与神经网络两种方法实现,并编写有GUI界面。(This paper mainly implements handwritten numeral recognition, using multiple logic regression and neural network to achieve two methods, and the preparation of a GUI interface.)