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number-recongnition
- 关于手写数字的识别问题，利用多种模式识别方法，例如神经网络方法，贝叶斯方法等-handwritten figures on the identification of problems and a variety of pattern recognition methods, such as neural networks, Bayesian methods
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。
HandwrittenDigitRecognitionBasedOnBPNeuralNetwork.
- BP神经网络，是利用人工智能的方法，训练权值，建立模式识别的模型。本程序，采用三层神经网络，对隐层的节点个数使用经验公式，对其他的参数设置也进行了优化，实现了手写数字的识别，
PatternRecong
- 图像模式识别的各种算法及其编程实现,包括模板匹配分类器、几何分类器和神经网络分类器等，可用于手写数字的识别。-A variety of image pattern recognition algorithm and its programming, including template matching classifier, geometric classifier and neural network classifiers, etc., can be used for handwritte
ann
- 用vc++编写的关于手写数字的识别的神经网络程序，能够识别，且识别率达 80-Prepared using vc++ handwritten digit recognition on the neural network program that can identify, and recognition rate 80
bpshuzishibie
- 采用神经网络实现数字识别，可用于车牌识别以及手写字符识别中-number recognize use BP network
BHanndwrittenP
- BP神经网络，是运用人工智能的方法，训练权值，建立模式识别的模型。本程序源码，使用三层神经网络，，对隐层的节点个数使用经验公式，对其他的参数设置也进行了优化，实现了手写数字的识别， 可直接使用。 -BP neural network, the use of artificial intelligence methods, training weights to establish the model of pattern recognition. The program source cod
CANeuralNetwoU
- CUDA应用：在CUDA上实现神神经网络，识别手写数字 -CUDA applications: the CUDA God neural network to recognize handwritten digits
fenlei
- 在VC++6.0环境下运行.手写数字的分类识别，并有详细的程序使用方法。分别采用模板匹配分类器，Bayes分类器，线性函数分类法，非线性分类，神经网络分类器进行识别，功能强大，还可以对比各种算法的优劣。-VC++6.0 environment run. Classification and recognition of handwritten digits, and a detailed program to use. Template matching classifier Bayes cla
DlgClassify
- MFC实现手写数字的识别，包含Beyes分类，线性函数分类，神经网络分类等各种算法的实现-MFC to achieve recognition of handwritten digits, including Beyes classification to achieve a linear function of classification, neural network classification of various algorithms
ssss
- 较实用的识别数字符号的实例，神经网络训练，识别手写数字-Identification of a practical instance of digital symbol, neural network training and recognition of handwritten Numbers
recognise
- 识别手写数字的人工神经网络的发展神经网络概念，如神经元，层，重量和反向传播等概念及c++实现在文中给出-This article chronicles the development of an artificial neural network designed to recognize handwritten digits. Although some theory of neural networks is given here, it would be better if you alr
shouxieshuzishibie
- 用于手写数字的识别，用Matlab编程，里面有数字样本和程序，用神经网络进行训练，已经运行成功。-For recognition of handwritten digits, Matlab programming, which has digital samples and procedures for training the neural network, has been run successfully.
handwrite_digit_recognition
- 简单的识别手写数字的demo，使用了神经网络进行训练-Simple recognition of handwritten digits demo
number-recognitionP
- 基于matlab利用BP神经网络开发的手写数字识别，正负样本为分别为1000张，手写数字是minist库-Based on BP neural network matlab developed handwritten numeral recognition, positive and negative samples were 1000, handwritten digital library is minist
CNN
- 用卷积神经网络实现的手写数字识别（minst）,可直接运行，识别率较高。用Tensorflow实现-Handwritten digital recognition (minst) with convolution neural network can be run directly and the recognition rate is high. Implemented with Tensorflow
ann
- 用简单神经网络(CNN)实现的手写数字识别(minst),可直接运行，用的是Tensorflow框架，通过该例程可以掌握Tensorflow基本用法-With a simple neural network (CNN) to achieve the handwritten numeral recognition (minst), can be run directly, using the Tensorflow framework, through the routine can master
main.py
- 人工神经网络入门 artificial neural network 使用sklearn 包实现分类图片，可用于手写数字识别(artificial neural network Using sklearn packet to achieve classification, can be used for handwritten numeral recognition)
neural_network.tar
- 用于识别手写的0~9，10个数字,使用的工具是matlab(used to identify handwritten number 0~9 ,ten digits)
MNIST数据集
- 手写数字识别数据集的训练集和测试集，关于BP神经网络(Handwritten digit recognition data set)