搜索资源列表
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)
gjrtc
- Computation Method D phononic bandgap plane wave, Energy entropy calculation, Transceiver contains two client programs.
mnist1
- 训练手写数字识别算法，正确率达到91.6%(Training handwritten numeral recognition)
神经网络mnist
- 利用神经网络对手写识别系统进行分类，正确率高达92%。(Using neural network to classify handwritten recognition system, the correct rate is as high as 92%.)
MNIST手写数字图片库
- 原图像库,未经过特征提取的手写数字库，可以使用(The original image library, untouched handwritten digital library, can be used)
mnist
- 深度学习时间手写数字识别，使用python和tensorflow实现(Handwritten numerals recognition in depth learning time)
Knn_train_mnist
- 利用Python实现Mnist数据集训练knn算法(Use Knn method to train mnist.)
Two-Layer-CNN-on-MNIST-master
- 卷积神经网络的matlab实现，同时可以作为图像处理使用，用于csi室内定位(Convolution neural network matlab implementation, can also be used as image processing for csi indoor positioning)
Handwritten_numeric_recognition
- 基于keras深度学习框架的手写数字字符识别(Handwritten numeric character recognition based on keras depth learning framework)
SAE
- 使用TensorFlow实现稀疏自编码神经网络，采用数据mnist(Using TensorFlow to realize sparse atuoencoder neural network, using data MNIST)
vae
- 变分自编码结构，用一个mnist数据。。。。。。(Using TensorFlow to realize Variational Auto-Encoder neural network, using data MNIST)
neural-networks-and-deep-learning-master
- 神经网络与深度学习相关代码 mnist数据集(neural-netword and deep-learning)
mnist
- 运行lenet的model进行深度学习计算(Depth learning calculation of model running lenet)
Logistic Regression
- Logistic Regression - a Classification method using the mnist DB, with sigmoid function and gradient ascent for optimization
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)
fisher
- 利用fisher方法实现手写体数字多分类识别，采用mnist数据集(simple program using fisher)
least_square
- 利用最小二乘法实现手写体数字识别，采用mnist数据集(simple program using least-square)
keras-dcgan
- keras平台下dcgan源码，包含配置文件，py文件，可直接运行训练网络，数据集为mnist手写数据集(Dcgan source code under the keras platform)
chinese_test
- 手写汉字识别，数据集训练，MNIST，Deep Convolutional Network识别手写汉字(Handwritten Chinese character recognition, data set training, MNIST, Deep Convolutional Network)
LeNet
- tensorflow实现手写体识别（包含mnist数据集）(Handwritten recognition by tensorflow)