搜索资源列表
test
- python实现用逻辑回归识别和分类人工手写数字-Classifying MNIST digits using Logistic Regression
beiyesigaijin
- 进过改进的贝叶斯分类器算法，识别手写数字，可以在画布内的任意位置手写。-Been to improve Bayesian classifier algorithm, digital handwriting recognition, handwriting can be anywhere within the canvas.
xianxingfenleiqi
- 使用线性分类器，实现手写数字0-9识别。-Using a linear classifier, 0-9 handwriting recognition.
svm_numberByHand
- 自己编写的一个matlab实现手写数字的识别-I have written a matlab achieve recognition of handwritten digits
handwriteREC
- 自己编写的一个matlab实现手写数字的识别，识别率高达90 以上。-I have written a matlab achieve recognition of handwritten digits recognition rate of 90 .
Classify
- 可用于识别手写数字，并有多种算法进行比较其识别正确率-Can be used for recognition of handwritten digits, and a variety of algorithms to compare the recognition accuracy
numberRec
- 按照模式识别系统组成，介绍手写数字自动识别技术的四个连续处理过程：数字图像预处理，特征提取，粗糙集特征约简和数字识别四个连续的过程。-In accordance with the pattern recognition system components, introduces four consecutive processing digital automatic handwriting recognition technology process: digital image prepro
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.
wenzishibie(ok)
- 用Matlab编写的用于手写数字的识别，里面有数字样本和程序，已经运行成功。-Identification using Matlab for handwritten numbers, there are digital samples and procedures have been run successfully.
NumberRecognition
- 采用模板匹配法进行手写数字的识别，是手写识别的基本方法，是学习手写识别技术的基础-To recognize handwritten numbers using the template matching method is the basic method for handwriting recognition, handwriting recognition technology is the basis of learning
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
handDigital
- 数字识别，提供训练好的HOG分类器，对单个手写数字进行识别-Digital recognition, to provide a good training HOG classifier, for a single handwritten numeral recognition
DBN
- 深度信念网络 (Deep Belief Network, DBN) 由 Geoffrey Hinton 在 2006 年提出。它是一种生成模型，通过训练其神经元间的权重，我们可以让整个神经网络按照最大概率来生成训练数据。我们不仅可以使用 DBN 识别特征、分类数据，还可以用它来生成数据。下面的图片展示的是用 DBN 识别手写数字： -Depth belief networks (Deep Belief Network, DBN) proposed by the Geoffrey Hinton i
chengx
- 关于手写数字的识别和手写字母的识别，有相关的程序-The recognition of handwritten digits recognition and handwriting letters, have procedures
BPshibie
- BP神经网络，用于手写数字的识别，非常实用，可以直接运行。-The BP neural network to handwritten digital recognition, very practical, can be directly run.
txmssb
- 手写数字的分类聚类的不同算法识别，应用的算法有人工神经网络，模糊识别等-number recognize
DigitsRecog
- 利用模式匹配算法，Bayes分类算法、LMSE、奖惩算法识别手写数字-Using pattern matching algorithm, Bayes classification algorithm, LMSE, recognition of handwritten numeral recognition algorithm
Digital-image-processing
- 数字图像处理，基于BP神经网络识别手写数字-Digital image processing, BP neural network based recognition of handwritten numbers
TrackStructure
- 手写体数字识别系统 可执行 c++ 输入图像应为bmp格式图片 可以在画图中手写数字然后保存放入程序中即可-c++
deeplearning
- 一个深度学习的python例程，该程序可以通过学习大量手写数字的数据提取出各手写数字的特征并对其进行识别。本文件中包含运行的主程序和结果，以及运行程序所需要的python库。- A depth learning python routines, the program can learn a lot of handwritten digital data extracted handwritten digits of each feature and gain recognition. Th