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Description: 基于神经网络的手写数字识别的源代码，绝对能够正常编译并运行！-based on neural network handwritten numeral recognition of the source code is absolutely normal to compile and run!
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Size: 207872 |
Author: 田巾 |
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Description: 针对MNIST数据库，但修改方便，可用于其他数字识别-For MNIST database, but modified to facilitate, can be used for other digital identification
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Size: 445440 |
Author: 黄健 |
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Description: 做手写阿拉伯字体识别时候需要用到图像数据文件。这时可以从http://yann.lecun.com/exdb/mnist/网站上下载数据源文件。这个程序可以很方便地将源文件读到matlab工作区间中去。-Arab make handwriting fonts needed to identify when the image data files. At this time http://yann.lecun.com/exdb/mnist/ site can be downloaded from the data source file. This procedure can be easily read the source file interval in matlab to work.
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Size: 1024 |
Author: 刘洋 |
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Description: 一个用来处理MNIST数据的工具，需要安装JAVA环境-MNIST data used to deal with a tool that will need to install JAVA environment
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Size: 3072 |
Author: wangdi |
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Description: 手写数字识别数据集，MNIST，包括原始数据集的所有样本，以及抽取的2000个样本的子集，.mat格式。美国著名数据集NIST的子集，模式识别常用实验数据集-handwritten digits recognition ,dataset, MNIST from NIST, .mat file,
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Size: 10696704 |
Author: 陈静 |
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Description: 该库的目标是提供一种易于使用的方法来训练和测试神经网络的MNIST数字（在浏览器或node.js中）。它包括10000个不同的mnist数字样本，通过建立这个以便与Synaptic开箱即用。可以通过MNIST数字加载器自由创建不同示例c的任何数字（从1到60 000）(The goal of the library is to provide an easy-to-use method to train and test the MNIST numbers of the neural network (in the browser or node.js). It consists of 10,000 different mnist digital samples, which are created by using this in order to be out of the box with Synaptic. You can freely create any number of different instances c (from 1 to 60,000) through the MNIST digital loader.)
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Size: 4903936 |
Author: 三陪
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Description: 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 Handwritten digital recognition is one of the application of pattern recognition. This paper introduces some of the main features of handwritten numbers and presents the truncation characteristics and uses the number of truncated features to experiment)
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Size: 11601920 |
Author: Ashley-d
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Description: 将官网打包好的mnist数据集转化成图片(translate mnist data to picture)
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Size: 20480 |
Author: zhuimenghx
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Description: tensorflow demo of mnist by python
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Size: 22255616 |
Author: Dl314
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Description: 这是MNIST的数据集，方便大家训练自己的模型(This is MNIST data set)
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Size: 16167936 |
Author: GeorgeCN
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Description: MNIST-classification-example
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Size: 12533760 |
Author: zhaodaima
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Description: CNN-mnist自制算法，使用卷积神经网络进行计算，准确率99.2(CNN-mnist is a algorithm written by yourself.A convolution neural network is used for calculation, the accuracy rate is 99.2)
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Size: 1024 |
Author: 风的追求
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Description: 自己的数据集制作,模仿mnist数据集，制作自己的数据集(based on the mnist dataset to make your own data)
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Size: 4096 |
Author: My.Hsiung
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Description: 包含训练用的图片数据包，python源代码，mnist实验，深度学习，进行图片分类(mnist experiment.python code.deep learning.picture classification,etc.)
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Size: 11268096 |
Author: 何CC |
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Description: mnist数据库通过整理下载后压缩到mnist,zip，适用于mnist自己调试解决自己的(The MNIST database is compacted and downloaded to MNIST, zip, suitable for MNIST itself to debug and solve its own)
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Size: 392192 |
Author: sgro |
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Description: 利用pycharm对mnist数据哭进行直接解压缩操作，得到所有的图片和标签(Using pycharm to wept MNIST data directly, get all the pictures and labels)
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Size: 10756096 |
Author: zhaoliang123 |
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Description: 用CNN识别MNIST数据集，test集正确率98.3%(Identifying MNIST datasets with CNN)
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Size: 16114688 |
Author: 王佳轩 |
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Description: mnist分类，python，tensorflow，深层神经网络(MNIST classification, python, tensorflow, deep neural network)
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Size: 1024 |
Author: yaya12138 |
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Description: 改进了官方的MNIST进阶demo，准确率提升。(The official MINIST advanced demo is improved and the accuracy is improved.)
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Size: 1024 |
Author: 怪物路飞 |
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Description: 基于python，利用主成分分析（PCA）和K近邻算法（KNN）在MNIST手写数据集上进行了分类。
经过PCA降维，最终的KNN在100维的特征空间实现了超过97%的分类精度。(Based on python, it uses principal component analysis (PCA) and K nearest neighbor algorithm (KNN) to classify on the MNIST handwritten data set.
After PCA dimensionality reduction, the final KNN achieved a classification accuracy of over 97% in a 100-dimensional feature space.)
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Size: 11599872 |
Author: 曲小刀 |
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