搜索资源列表
CUDA-CNN-master
- CNN cuda的加速。 start-of-art结果的流行的数据集 1。测试mnist并获得99.76 ,投票后(99.82 )(最好的99.79 ) 2。测试cifar-10并获得81.42 最好(90 ) 3。测试cifar - 100和51.13 (最好的65 )-CNN accelerated by cuda. The start-of-art result s of popular datasets 1. Test on mnist and get 99.76
CUDA-CNN-master
- 提升mnist字符识别准确度，利用cuda进行加速其识别过程-improve the accuracy of mnist
CNN
- 用 卷积神经网络进行手写字符 识别,内含mnist训练集-Handwritten character recognition, containing mnist convolution neural network training set
CNN-MINIST
- 利用卷积神经网络进行MINIST数据集的分类识别，MATLAB源程序。-Convolution neural network classification MNIST dataset, MATLAB source.
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.
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
CNN
- 一个卷积层+一个下采样+softmax实现mnist识别(implement a simple CNN)
tensorflow-cnn
- 基于TensorFlow的mnist数据集识别，使用CNN的方法，采用梯度下降学习(MNIST data set recognition based on TensorFlow, using CNN method, using gradient descent learning)
code
- 使用HLS实现的能进行手写识别的CNN网络，使用的是MNIST数据集(Realize CNN network using HLS tool)
Two-Layer-CNN-on-MNIST-master
- CNN 训练手写字,Matlab 代码。(CNN manual character)
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)
CNN_MNIST
- Tensorflow实现基于MNIST数据集的卷积神经网络(Tensorflow implementation of convolutional neural networks based on MNIST data)
mnist_uint8
- CNN卷积神经网络中mnist-uint8(deepLearnToolbox-master)
code&doc
- 基础的卷积神经网络代码，实现mnist手写字符识别，含中文文档说明(Basic CNN code, including detailed annotation in Chinese)
cnn
- 卷积神经网络（CNN），TensorFlow框架下运行，基于MNIST手写体数据集，可直接运行(Convolutional Neural Network (CNN), run under TensorFlow framework, can run directly based on MNIST handwritten dataset)
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)
minst_cnn
- CNN MNIST (include mnidt dataset)
CNN
- 手写体识别的训练，采用卷积神经网络，附带数据集下载代码(The training of handwritten recognition is based on convolution neural network, and the download from the dataset.)
MNIST
- 用CNN识别MNIST数据集，test集正确率98.3%(Identifying MNIST datasets with CNN)
Two-Layer-CNN-on-MNIST-master
- cnn Mnist 两层卷积实现，可以达到97%d 识别率，大家可以拿来上手试用(CNN MNIST two layers)