Convolution Fundamental I Foundations of CNNs Learning to implement the foundational layers of CNN's (pooling,convolutions) and to stack them properly in a deep network to solve multi-class image classification problems. Computer vision Computer visi…

Practical Advice Using Open-Source Implementation We have learned a lot of NNs and ConvNets architectures It turns out that a lot of these NN are difficult to replicated. because there are some detail that may not presented on its paper. There are so…

前言 理论知识:UFLDL教程和http://www.cnblogs.com/tornadomeet/archive/2013/04/09/3009830.html 实验环境:win7, matlab2015b,16G内存,2T机械硬盘 实验内容:Exercise:Convolution and Pooling.从2000张64*64的RGB图片(它是the STL10 Dataset的一个子集)中提取特征作为训练数据集,训练softmax分类器,然后从3200张64*64的RGB图片(它是th…

Computer Science An Overview _J. Glenn Brookshear _11th Edition Universal Programming Languages In  Chapter  6  we  studied  a  variety  of  features  found  in  high-level  programminglanguages. In this section we apply our knowledge of computabilit…

卷积的实现: 对于每幅图像,每个filter,首先从W中取出对应的filter: filter = squeeze(W(:,:,filterNum)); 接下来startercode里面将filter旋转90度并且取出image: % Flip the feature matrix because of the definition of convolution, as explained later filter = rot90(squeeze(filter),2); % Obtain the…

Understanding Convolution in Deep Learning Convolution is probably the most important concept in deep learning right now. It was convolution and convolutional nets that catapulted deep learning to the forefront of almost any machine learning task the…

3.Spark MLlib Deep Learning Convolution Neural Network (深度学习-卷积神经网络)3.1 http://blog.csdn.net/sunbow0 Spark MLlib Deep Learning工具箱,是依据现有深度学习教程<UFLDL教程>中的算法.在SparkMLlib中的实现.详细Spark MLlib Deep Learning(深度学习)文件夹结构: 第一章Neural Net(NN) 1.源代码 2.源代码解析 3.实例 第…

1.Introduction 2.Convolution 3.Deconvolution 4.Summary…

在学习cnn的过程中,对convolution的概念真的很是模糊,本来在学习图像处理的过程中,已对convolution有所了解,它与correlation是有不同的,因为convolution = correlation + filp over in both horizontal + vertical 但在CNN中,明明只是进行了correlation,但却称之为convolution,实在不解 下面, 将图像处理中的convolution重新整理记录 因为网络关于这部分的解释很多,这里直接…

(1) 定义计算过程中需要的symbolic expression """ 定义相关的symbolic experssion """ # convolution layer的输入,根据theano,它应该是一个4d tensor input = T.tensor4(name='input') # 共享权值W,它的shape为2,3,9,9 w_shp = (2,3,9,9);w_bound = numpy.sqrt(3*9*9) W = thea…