搜索资源列表
xmain
- 用matlab写的印刷体数字识别程序，对matlab 6.0以上有效-Written with matlab print digital identification procedures, more effective on matlab 6.0
bp
- MATLAB 神经网络用于数字识别源程序 手写数字识别-MATLAB neural network for digital identification of the source handwritten numeral recognition
bp
- 基于神经网络的手写数字识别技术研究 论文详解-Neural network-based Handwritten Digit Recognition Technology
VCnunRecognition
- VC手写数字识别代码，采用的是欧式距离法-VC handwritten digital code, using the Euclidean distance method
vc
- 该文件为数字识别系统的源代码，用VC++程语言序编写，可直接运行。-The file is in digital identification system source code, using VC++ programming language written procedures, can be directly run.
thintwo
- 数字识别，区分图片0到9，共有一百幅图片，一部分用来训练，一部分用来测试-Digit recognition, the distinction between image 0 to 9, a total of one hundred pictures, some for training, in part to test
num
- 利用matlab采用基于Gabor特征的识别算法实现手写数字识别-Using matlab recognition based on Gabor feature recognition algorithm for handwritten numeral
classify
- 机器学习中关于分类的一段matlab程序，自己的课后大作业，是关于手写数字识别-Machine learning matlab on a classified program, their major job after school, on the handwritten numeral recognition
bp
- BP神经网络的手写数字识别 识别数字为0~-BP neural network recognition of handwritten numeral recognition numbers from 0 to 99
hopfield
- 离散二值神经网络，作为一种新的人工神经网络，是一种具有联想记忆功能的网络，用于数字识别。-Discrete binary neural networks, as a new artificial neural network is a kind of associative memory function of the network, for digital identification.
recognition
- 基于MATLAB的手写体数字识别，有需要数字识别程序的可以下载啊-NeuralNetwork_BP_shibie
myBPMNIST
- 采用典型的BP算法实现了有导师学习下的神经网络，采用输入层、隐含层和输出层的三层结构，实现了BP算法。并用此算法实现了基于MNIST的数字识别，采用7000个样本做训练，自洽检验正确率达到了99.79%。
BP算法的手写数字识别
- 简单的应用gui界面编写的数字识别。。。。。。
手写数字识别 matlab
- 手写数字识别 matlab，用于进行数字识别，是机器学习现在的热门话题
5，ATKNCR(数字字母手写识别库)
- 数字字母手写识别库 可用于显示数字字母等(Digital alphabet handwriting recognition library)
BP 0-9识别
- 本程序由matlab编写，以BP神经网络进行0~9十个数字的识别。(This procedure written by MATLAB, BP neural network for 0~9 ten digital identification)
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
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.)
neuralnetwork-sample
- 由java编写的，具有gui界面的，手写数字识别神经网络示例(Written by Java, with GUI interface, handwritten numeral recognition neural network examples)
train-labels-idx1-ubyte
- 用于手写数字识别的训练数据（标签） 数据格式：前32位为2049，再32位为数据数量，之后每一位都是标签值(Training data (tags) for handwritten digit recognition)