搜索资源列表
patternRecognitionAndcompute
- 模式识别与智能计算matlab实现的源代码 主要有聚类分析 手写数字分类的实现-pattern Recognition And intelligence computing
numberrecogition
- 手写数字识别 实现简单的手写数字识别功能-Handwritten numeral recognition simple handwriting recognition feature number
digitalrec
- 手写数字识别程序，根据手写鼠标移动的方向，判读输入的数字，可以识别0-9等阿拉伯数字，识别率90 以上-Handwritten numeral recognition program, according to the direction of the handwriting mouse movement, interpretation of the input figures, can be identified 0-9, etc. Arabic numerals, the recogniti
number_recognition_Fisher
- 利用Fisher线性判别式，进行手写数字的识别。-Fisher linear discriminant handwritten numeral recognition.
handwriting_recognize
- 能够识别手写数字，手写字符，识别率达到90 以上，很好用的-Able to recognize handwritten numbers, handwritten character recognition rate of 90 or more, the good
Recognition
- 手写数字识别(用matlab编写的，能识别普通的0-9）这10个数字。-Handwritten numeral recognition
clj
- 利用统计特征方法中的基于正态分布的最小错误率贝叶斯分类器实现简单的手写数字识别应用程序-digital recognition
DigitsRec_HOG_SVM
- svm的手写数字识别，是一个用于数字识别的例子-svm shuzishibie
RegFigure
- MFC手写数字识别程序，记录笔画及书写方向来区分不同的数字。-MFC handwritten numeral recognition program, recording strokes and written directions to distinguish the different figures.
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
opencv 的手写数字字符识别
- 基于opencv 和机器学习方法的手写数字字符识别(Handwritten numeral character recognition of opencv)
MNIST
- 简单的手写数字识别，在深度神经网络中的简单尝试，对于初学者有个很好的理解(Simple handwritten numeral recognition, in the depth of neural network simple attempt, for beginners have a good understanding)
手写数字识别系统
- 基于神经网络识别的手写数字识别系统，有gui界面(Handwritten digital recognition system based on neural network recognition)
simplecharrec(III)-update
- 基于PCA和BP网络的手写数字字符的识别(Recognition of handwritten numeric characters based on PCA and BP networks)
基于机器学习的手写数字识别
- 基于Python机器学习的手写数字识别 基于Python机器学习的手写数字识别(Handwritten digit recognition based on Python machine learning Handwritten digit recognition based on Python machine learning)
mnistA
- 手写识别，基于tensorflow的代码，包含数据源等，供学习，代码为官方源代码(Handwriting recognition, tensorflow based code, including data sources, etc. for learning, the code is official source code)
手写数字样本
- 关于手写数字的两个样本库，可利用多种语言进行图片的识别处理。(Two sample libraries for handwritten numbers)
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))
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)