搜索资源列表
CNN-for-Segmentation
- 一篇关于如何用卷积神经网络（CNN）进行图像分割的论文，里面得到的效果还可以-an article about how to use CNN for image segmentation.The result is not bad.
cnn
- 用于图像分类的源代码，深度学习的应用，cnn卷积神经网络的使用，可以自己更换数据集或者调优，适合初学者使用！-For image classification of the source code, the application of in-depth learning, cnn convolutional neural network, you can replace the data set or tuning, suitable for beginners!
cnn
- CNN网络关于手写数字识别的全套程序，可以自行调节迭代参数，得到自己想要的结果。-The simulation about the CNN experiment in Matlab.
CNN
- 手写数字识别 lenet 5 CNN的代码，对于初学机器学习者非常有帮助,可以运行。-Handwritten numeral recognition lenet 5 CNN code, for beginners machine learners very helpful, you can run.
cnn-text-classification-tf-master
- 深度学习实现算法，卷积网络，文本分类，python代码实现-deep learning alg，cnn,text classification,very very useful
face-CNN
- 自己编写的CNN程序，包括怎么创建数据集-I have written CNN program, including how to create a data set
Event-Extraction-via-CNN
- 此论文使用卷积神经网络对文本中的长句进行信息抽取，比如抽取主谓宾等-this paper is using for information extraction by cnn
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
- CNN learning 手写数字识别 神经网络-CNN learning handwritten numeral recognition neural network
CNN
- CNN - Convolutional neural network class This project provides matlab class for implementation of convolutional neural networks. Deep Neural Network It provides deep learning tools of deep belief networks (DBNs). myCNN is a Matlab implementation
CNN
- CNN 卷积神经网络，是深度学习的理论基础，能帮助加深对深度学习的认识.-CNN is the basis of deep learning. It can help researches to get better understanding of deep learning.
CNN
- CNN(CondensedNearestNeighbor)是最早的基于近邻分类的实例选择算法。本程序实现了CNN算法，能很好的实现近邻分类的实例选择。-CNN (CondensedNearestNeighbor) is the earliest instance selection algorithm based on nearest neighbor classification. The core idea of the algorithm is that if the instance c
CNN
- CNN卷积神经网络的matlab实现，CNN主要用来识别位移、缩放及其他形式扭曲不变性的二维图形。并附有相关说明-Realization of CNN Convolution Neural Network by,CNN is mainly used to identify displacement, zoom and other forms of twisted invariance of the two-dimensional graphics, With instructions
Image retrieval
- 基于内容的图像查询，采用卷积神经网络，CNN代码使用了matconvnet工具包，包括代码和实验报告。(Content based image query, using convolutional neural networks, CNN code, using the matconvnet toolkit, including code and experimental reports.)
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)
CNN Matlab代码
- 利用大量图像数据对卷积神经网络算法进行训练，通过卷积、池化、下采样以及全连接层训练后的卷积神经网络在图像识别精度越来越高。(By using a large number of image data to train the convolutional neural network algorithm, the accuracy of the image recognition is higher and higher by convolution, pooling, down sampling
Bilinear-CNN-TensorFlow-master
- 双线性cnn的实现过程,使用的是tensorflow的算法框架,在特征融合方面的一种创新(Bilinear CNN implementation process, using the tensorflow algorithm framework, in terms of feature integration in an innovation)
yuputu
- 语音的语谱图实现，用于语音转换语谱图，用CNN网络进行分类识别(Realization of phonological representation of speech)
cnn-cbir-benchmark-master
- python语言，使用卷积神经网络的特征做图像检索(image retrieval using CNN)
CNN_impl
- cnn算法的手写实现，教你如何一步一步实现cnn算法，理解cnn原理(CNN algorithm handwritten realization, teach you how to step by step to achieve the CNN algorithm, understand the CNN principle)