搜索资源列表
MyCnn
- 用VS2012实现手写数字识别的卷积神经网络算法，用mnist库作为输入-Using VS2012 to achieve the handwritten numeral recognition of the convolution neural network algorithm, using the MNIST library as an input
CNN
- 深度学习的卷积神经网络的MATLAB代码实现，数据为MNIST标准库。-it s a code in CNN with matlab.the is the MNIST.
q5
- train 2 layers neural networks to recognize MNIST of digits handwritten-train 2 layers neural networks to recognize MNIST of digits handwritten
MNIST-OCR-ELM
- ELM超限学习机的拓展应用，多层感知机，可用于特征提取- Expand the application ELM overrun learning machine, MLP can be used for feature extraction
Demo-MNist
- 利用神经网络进行手写数字识别演示代码！非常具有代表性！-Using neural network Digital Recognition demo code!
MatConvNet-mr-master
- 牛津大学开发的matconvnet工具包，可以生成vgg，alexnet等等模型，imagenet，mnist多种数据集可以跑-Oxford University developed matconvnet toolkit can generate vgg, alexnet etc. model, imagenet, mnist multiple data sets can be run
input_data
- 机器学习领域中常用的数据集MNIST的下载代码-Commonly used in the field of machine learning dataset MNIST download code
mnist
- this code is about mrs method
Softmax_exercise
- Softmax用于多分类问题，本例是将MNIST手写数字数据库中的数据0-9十个数字进行分类，其中训练样本有6万个，测试样本有1万个数字是0~9-Softmax for multi classification problems, the present case is the handwritten data MNIST digital 0-9, classification, training samples which have 60,000, there are 10,000 test
bpback
- 神经网络比较基础的算法，实现梯度下降和反向传播，以及L2规范化、交叉熵代价函数的引入，卷积神经网络 该算法用于mnist数据测试，有详细中文注释-Neural network based on the comparison algorithm, gradient descent and back-propagation, and L2 standardization introduced cross entropy cost function, convolution neural netw
tiny-dnn-master
- cnn卷积神经网络实现mnist的手写体识别程序-CNN convolution neural network to realize mnist handwritten recognition program
NN-Back-Propagation-Generalized
- Solving XOR-problem and consecutively try MNIST-dataset with fundamental level of understanding on neural networks. Recommendable for beginners ( As I am :) ) And it s fully documented.
deep-belief-network
- 训练一个深度网络，并应用于MNIST库上进行字体识别-Training a deep autoencoder or a classifier on MNIST digits
CNN
- 使用CNN卷积神经网络来训练MNIST数据集-CNN convolution using neural network training data set MNIST
MLP
- 使用MLP多层神经网络来训练MNIST数据集-Use MLP multi-layer neural network training data set MNIST
softmax
- MATLAB实现softmax,测试类主要采用mnist-implement a simple softmax in matlab
MNIST_classify
- 使用决策树，支持向量机以及人工神经网络完成对MNIST手写数字体的分类。-Using a decision tree, support vector machines and artificial neural network to classify the number of MNIST handwritten font.
MNIST(tensorflow)
- 基于tensorflow的手写识别，训练后可以识别手写数字-Based on tensorflow handwriting recognition, training can identify handwritten numbers
medrankDB
- 基于mnist数据库，对其用C++实现b+树索引和medrank搜索。data需要到mnist网站下下载-Based mnist , search for them using C++ achieve b+ tree indexes and medrank. data need to download website under mnist
caffe-master
- caffe深度学习框架 内置mnist、cifair-10数据集-caffe deep learning framework