搜索资源列表
handprint_recognition
- 关于联机手写数字识别的C++源代码,可以对手写体数字库进行识别。-figures on the on-line handwriting recognition to the C source code, can figure on the handwritten identification.
handwriting_recognition
- unix下的手写体识别程序,识别效果不错。可以识别英文和数字。
HDigitalRReca
- 手写体数字识别的Visual C实现使用神经网络算算法对手写体数字进行识别,训练后识别率可达90%左右。 -Handwritten numeral recognition, Visual C Neural Network Algorithm for recognition of handwritten digit recognition rate after training up to about 90 .
Hand-writes-number-recognition
- 用C++写的手写数字识别程序,能够比较准确的识别大部分手写体数字。-Written by C++ handwritten numeral recognition program that can more accurately identify most of the handwritten numerals.
dataset_618531
- 包含1593手写体数字0 ~ 9。从semeion.data通过MATLAB semeion.mat,可以直接使用。原semeion.names为自述。M。 Mat:1593×266 每一个行为样本,其中256是手写数字的16×16,在10栏的数字识别标签,例如:如果第一行是1,然后是0号,其次是1,1。等等。 在Matlab的小例子,可以得出每一个数字,一个更好的理解。你想翻转和旋转的是写作的习惯相一致的图像。-Contains 1593 handwritten digit 0~9
handwritten-digits_recognition-
- 一个基于神经网络的手写体数字识别的matlab程序,可以自行进行神经网络训练并识别给出相应的结果-A neural network-based handwritten numeral recognition matlab program, the neural network can be trained to identify themselves and give the corresponding results
Handwritten-numeral-recognition
- matlab环境下实现对手写体数字的分类识别-Handwritten Arabia digital numeral recognition
asdfgh
- 实现数字识别,径向基神经网络手写体数字的识别准确率高-Digital recognition, RBF neural network handwritten digital recognition accuracy is high
SVM-handwritten-digits-recognitio
- 介绍了在提取穿越次数特征、粗网格特征以及密度特征提取的基础上应用SVM进行手写体阿拉伯数字识别的方法。-Introduced the extraction across a number of features, coarse grid and density feature extraction on the basis of the application of SVM method for handwritten digits recognition.
shibie
- 手写体数字的识别,采用bp神经网络,有很好的效果-Recognition of handwritten digits, using bp neural network, the results were OK
handwriting
- 手写体识别系统,用于对0-9的数字识别出正确率-Handwriting recognition system, for 0-9 identify the correct rate
11
- 手写体识别_模板匹配识别方法,通过matlab实现基于神经网络的手写数字识别-Handwriting recognition _ template matching method, the matlab implementation of handwritten digit recognition based on Neural Network
kuaisushouxietishuzizifushibie
- 通过模拟人眼识别数字字符的过程,提出了一种基于字符整体特征的快速手写体数字字符识别方法。此方法不需要对字符图像做复杂的细化处理,减少了细化形变可能带来的误识和拒识,也不需要进行复杂的笔道特征分析,因此速度很快。同时,由于不同人书写的数字字符的整体特征都相同,因此此方法的识别率也非常高。-n this paper, a fast handwritten digital character recognition method based on the overall character of ch
ML_project
- 程序是对手写体数字进行识别,用knn算法,代码编写是用java。训练样本和验证样本都在代码中提供了。-The program is to handwriting figures to identify, with knn algorithm, the code is written with java. Training samples and validation samples are provided in the code.
OCR
- OCR 数字识别 自由手写体 离线 matlab平台 识别0-9的数字(OCR digital recognition free handwritten off-line matlab platform to identify 0-9 numbers)
digital
- 实现手写体识别,并且使用自己手写的数字作为验证,得到了比较好的结果(digital recognition we get a good result at the test of our own digital writing and use the language of pyton)
Run_MNIST
- 下载MNIST数据集(手写体数字0-9)后,搭建卷积神经网络,将输入的数据集经过一层一层的卷积,到最后计算交叉熵,用梯度下降算法去优化它,使它变得最小,这就训练出了权重和偏置量,识别的准确率为91%(Download the MNIST data set (handwritten number 0-9), build a convolutional neural network, the input data set by convolutional layers, finally calcul
MNIST_data
- MNIST数据集是一个手写体数据集,这个数据集由四部分组成,分别是一个训练图片集,一个训练标签集,一个测试图片集,一个测试标签集;我们可以看出这个其实并不是普通的文本文件或是图片文件,而是一个压缩文件,下载并解压出来,我们看到的是二进制文件。其中包含60000张手写体识别数字图片。(MNIST data set is a handwritten data set, which consists of four parts: a training picture set, a training l
DeepLearnToolbox-master
- CNN,DBN算法可以对手写体数字进行识别,准确率高(CNN and DBN algorithm can recognize handwritten numerals with high accuracy)
手写体识别/python
- 此程序使用的是python语言,能对手写数字0~9进行识别。