搜索资源列表
MATLAB实现手写数字识别
- 基于MATLAB实现简单的手写数字(0-9)的识别程序。属于模式识别内容
手写鉴别用VC++6.0开发
- 手写鉴别用VC++6.0开发的一个手写字符识别系统,联机输入签名,可以识别数字,字母和汉字. ,Handwriting identification using VC++ 6.0 Development of a handwritten character recognition systems, on-line input signatures can identify numbers, letters and Chinese characters.
weewe
- 手写数字识别系统,好好用的,希望大家喜欢哈-Handwritten numeral recognition system, properly used, I hope everyone likes Kazakhstan
delphi5
- 模板匹配之手写数字识别系统,基于DELPHI 7.0-Template matching of handwritten numeral recognition systems, based on DELPHI 7.0
NeuralNetwork_BP
- 模式识别的一个基础程序,手写数字模式识别,提供给大家分享-A basic pattern recognition procedures, handwritten numeral recognition, available to everyone to share
RegFigure
- MFC编写的手写数字识别程序,可移植到wince下-MFC prepared handwritten numeral recognition procedure can be transplanted to wince under the
12
- 手写数字识别系统设计,主要用于对手写体数字的自动识别-Handwritten numeral recognition system design, mainly used for automatic recognition of handwritten numerals
2143-anqn
- 数字识别vc++实现的手写数字识别算法,给做图像处理的朋友一个参考。该程序能识别-noWith vc++ Realize the handwritten numeral recognition algorithms, image processing to make friends as a reference. The program can identify 0 ~ 9 of 10 digits.
tensorboard
- tensorflow手写数字识别,提高识别的准确率(Tensorflow handwritten numeral recognition, improve the accuracy of recognition.)
cnn
- 手写数字识别的简单实现,CNN入门到深入,三个版本供读者使用。(Simple Implementation of Handwritten Number Recognition, Getting Started with CNN)
R语言 svm 手写数字识别
- 用R语言写的手写数字识别算法(svm 方法)(Handwritten numeral recognition algorithm written in R language (SVM method))
CNN
- 手写数字识别的数据集 matlab实现cnn(Data Set for Handwritten Number Recognition Realization of CNN in matlab)
手写数字识别
- 运用卷积神经网络进行特征提取,然后进行分类(Using convolution neural network to extract features and classify them)
实验四
- LeNet神经网络 手写数字识别 下载数据集代码 数据集下载完成的(Handwritten Number Recognition Based on LeNet Neural Network)
1111
- 基于PCA的手写数字识别源码,内附有说明文件,非常清晰!运行环境:matlab。(Handwritten digital character recognition based on PCA and BP network)
BP_mnist_UI-master
- 基于BP神经网络的手写数字识别,有完整代码(based image segmentation algorithm)
深度学习CNN手写数字识别
- 利用CNN网络手写数字识别,注释清楚,损失函数用的是focalloss,标注明确,可以跑通,框架是pytorch
手写数字识别
- 简单的神经网路学习入门学习资料,使用bp神经网络进行手写数字识别。
神经网络-手写数字识别
- 利用BP神经网络,对MNIST数据集中的5000张图片进行训练,实现手写数字识别,训练出来的结果准确率在90%。
minist手写数字识别,搭建3层的卷积神经网络
- minist手写数字识别,基于Keras搭建3层的卷积神经网络,达到99%的识别准确率,且绘制相应的准确率和loss function曲线;