搜索资源列表
mnist
- mnist手写体数据库，适合用于做手写数字方面的实验-mnist handwritten database suitable for doing experimental aspects of handwritten digits
Mnist
- mnist在MATLAB中的调用。直接加载.mat文件就可以。-mnist call in MATLAB. Files can be loaded directly .mat.
mnist-master
- 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 netwo
lenet_iter_10000
- caffe-windows mnist 训得到的模型，可用于手写字体识别(Caffe-windows MNIST training model can be used for handwritten font recognition)
mnist_train_leveldb
- caffe-windows mnist 训练用的数据集，此数据集用于mnist训练模型(Caffe-windows MNIST training data set, this data set is used for MNIST training model)
mnist_test_leveldb
- caffe-windows mnist 测试用数据集，此数据集用于mnist训练时的测试数据集(Data sets for caffe-windows MNIST tests, which are used for test data sets when MNIST is trained)
visulize
- caffe-window matlab 接口训练mnist后权重、特征可视化(Caffe-window Matlab interface training MNIST.M file, MATLAB platform training MNIST model)
codecnnMNIST
- 用cnn卷积神经网络实现对mnist手写库的识别(mnist classfication with convolution neural network)
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
mnist
- tensorflow demo of mnist by python
mnist_uint8
- CNN卷积神经网络中mnist-uint8(deepLearnToolbox-master)
mnistDemo.py
- 实现tensorflow的mnist实现(The file use tensorflow implement mnist)
mnist_data
- 介绍mnist数据,可以了解该数据，用于具体的训练(introduce mnist data)
code
- 基于python的mnist数据集的读取，以及转换为csv形式(Python based MNIST data set read, and converted to CSV form)
cnn-mnist
- 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)
MNIST
- mnist手写体识别，使用tensorflow编写(mnist hand-writing recognition using tensorflow)
bpnn
- 用Python3实现BP神经网络对MNIST数字手写体识别，下载就能用(Using Python3 to implement BP neural network for MNIST digital handwriting recognition, download can be used)
mnist
- 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)
minst_cnn
- CNN MNIST (include mnidt dataset)
mnist
- 基本的dnn，准确率有百分之93左右，有注释(Basic DNN, the accuracy rate is ninety-three percent)