搜索资源列表
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
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)
tensorflow_cov_mnist
- 基于tensorflow的mnist数据集卷积神经网络简单代码实现。(MNIST dataset based on tensorflow convolutional neural network simple code implementation)
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)
Tensorflow：实战Google深度学习框架
- 介绍tensorflow的应用，mnist数据，神经网络的简单例子(Describes the application of tensorflow, MNIST data, a simple example of neural networks)
test
- tensorflow测试 计算mnist识别准确率 以及计算时间(tensorflow test Calculate the MNIST recognition accuracy and calculation time)
dnn
- 用TensorFlow搭建神经网络，识别手写数字(building the neural network by using TensorFlow to identify mnist dataset)
AlexNet
- 使用TensorFlow 实现 AlexNet ，并使用 Mnist 数据集进行训练并测试。(AlexNet is implemented using TensorFlow and trained and tested using the Mnist data set.)
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)
5.2.2.py
- MNIST数字识别问题 使用验证数据集判断模型结果(tensorflow.examples.tutorials.mnist After 30000 training step(s), test accuracy using average model is 0.9835)
LeNet5MNIST
- 使用TensorFlow处理MNIST数据，帮助更好的理解和使用TensorFlow(Using TensorFlow to process MNIST data to help better understand and use TensorFlow)
lenet_test
- 包含mnist数据集的lenet例子,快速训练部分数据,达到85%的准确率(A lenet example that contains the MNIST dataset to quickly train part of the data to reach a 85% accuracy rate)
dbn_tf-master
- 利用深度置信网络实现对mnist数据集的分类(sort out the set of mnist with DBN)
ALEXNET
- 搭建的一个AlexNet的网络结构，包含原始AlexNet的最基本结构，使用的数据集为mnist，所以对其中的参数做出较小的修改，搭建网络方式比较典型，可根据范例结构自行扩展（包括原始mnist数据）(Build an AlexNet network structure, including the most basic structure of the original AlexNet, using a data set of mnist, so the parameters of the s
tensorflow-mnist
- 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.)