搜索资源列表
CNN
- 细胞神经网络，简称为CNN，由于其能够产生混沌吸引子，而被广泛应用于加密系统中，本代码为画出CNN的超混沌吸引子。-Neural networks, referred to as CNN, due to its ability to generate chaotic attractor, and is widely used encryption system, the code for drawing CNN super chaotic attractors.
DeepLearnToolbox-master
- 深度学习代码，有各种深度学习的模型。有卷积神经网络，稀疏自动编码-it is a DeepLearnToolbox，we can see cnn,sae,dbn,sae in this zip.
CNN
- matlab DeepLearnToolbox cnn工具箱代码-cnn tool
CNN
- 这是个卷积神经网络的实现代码，对手写体进行识别，现在正确率可以达到90 -This is a convolution neural network implementation code of conduct handwriting recognition accuracy rate is now 90
CNN
- 此代码是对卷积神经网络用于手写字体识别的实现，程序是基于theano库开发的，并且用到了集成化模块keras,方便我们构建自己的网络结构，很好的解决分类问题-This code is the convolution neural network for handwritten character recognition, the program is based on the theano library development, and use the integrated modular k
FPGA-CNN-master
- fpga硬件实现cnn代码，学习可用。了解基本的深度学习概念和实现方法(FPGA hardware implementation of the code, used for learning)
cnn
- 这是一个经过自己整理的卷积神经网络的代码，对0-9数据集进行分类的代码，使用tensorflow框架完成的，主要使用的语言是Python，可以直接运行，初学者可以用于学习交流。(This is a self compiled convolutional neural network code, 0-9 data sets for classification of code, using the tensorflow framework to complete, the main languag
代码
- 简单在线学习模式下的CNN算法，适合初学者(See the convolution neural network algorithm again find my learning mode, is a beginner to use)
CNN
- 入门级的CNN学习代码，包含了完整的测试数据及注释(Entry-level CNN learning code, including the complete test data and notes)
Char-RNN-PyTorch-master
- # Char-RNN-PyTorch 使用字符级别的RNN进行文本生成，使用PyTorch框架。[Gluon实现] ## Requirements - PyTorch 0.2 - numpy ## Basic Usage 如果希望训练网络，使用如下的代码 ```bash python main.py \ --state train \ --txt './data/poetry.txt' \ # 训练用的txt文本 --batch 128 \ # batch_siz
cnn_exercise
- 深度学习CNN代码,帮助理解卷积网络，代码是可以运行的，没有问题(Deep learning CNN code to help understand the convolution network, the code is running, no problem.)
tensorflow实战代码
- Tensorflow新手学习代码，包括AutoEncoder, CNN, DenoisingAutoEncoder, ImageToNum, MLP, softmax_regression,tensorboard 等(Tensorflow codes for novices, including AutoEncoder, CNN, DenoisingAutoEncoder, ImageToNum, MLP, softmax_regression, tensorboard, etc.)
卷积神经网络CNN代码解析-matlab
- 卷积神经网络CNN的代码解析文档，可以辅助了解CNN的MATLAB程序实现过程(CNN code analysis document of convolution neural network)
market_evaluation
- 可以对已经训练好的CNN模型进行特征提取，并且对提取得到的图片特征进行性能识别(Feature extraction can be performed on the trained CNN model, and performance identification of the extracted image features can be performed.)
tensorflow-resnet-master
- 残差神经网络的代码，可以用，非常好，，，，，，。(resual CNN about deep learning ,very good.........................)
Deep learning_CNN DBN RBM
- 运用深度学习模型实现图像的分类，主要包括卷积神经网络CNN和深信度网络DBN(Classification of images using deep learning model includes convolutional neural network CNN and belief network DBN.)