CNN(convolutional neural networks)是Deep Learning在计算机视觉领域的一个成功模型结构,当然不止计算机视觉,语音识别或者文本识别等领域也可以应用,但在计算机视觉领域应用最为广泛,也更为成熟。本文尝试从简单的图像处理方法入手,进而引出CNN的结构和处理方法,最后探讨下谷歌的Alpha-Go是如何采用CNN结构进行训练的。 1、...
Deep learning: A subset of machine learning in which multilayered neural networks learn from vast amounts of data. How Do CNNs Work? Convolutional neural networks work by ingesting and processing large amounts of data in a grid format and then extracting important granular features for classificat...
self.input=input#there are "num input feature maps * filter height * filter width"#inputs to each hidden unitfan_in = numpy.prod(filter_shape[1:])#维度拉成列,每个元素都为一个像素,fan_out同理#each unit in the lower layer receives a gradient from:#"num output feature maps * filter h...
实际上在deep learing 里经常说的convolution 对应的是数学概念里的cross-correlation, 两者的区别是,数学里的convolution 比cross-correlation 多一步对filter翻转的操作. 也就是说deep learning里的convoluton 叫做cross-correlation更确切一些。但是翻转那一步对deep learning 没有影响,所以deep learning 里就用convolutio...
降噪学习(1):Kernel-Predicting Convolutional Networks for Denoising Monte Carlo Renderings 前言 降噪系列的第一篇学习笔记,阅读一篇运用Deep learning进行图像降噪的工作 整篇论文难度不大,但是笔者花了很多时间(补足前置知识、弄清架构、理清数学公式) 有些许概念笔者未完全理解,之后抽空更新...
Technically, the convolution as described in the use of convolutional neural networks is actually a “cross-correlation”. Nevertheless, in deep learning, it is referred to as a “convolution” operation. Many machine learning libraries implement cross-correlation but call it convolution. — Page ...
Deep Learning – which has emerged as an effective tool for analyzing big data – uses complex algorithms and artificial neural networks to train machines/computers so that they can learn from experience, classify and recognize data/images just like a human brain does. Within Deep Learning, a C...
From the series:Introduction to Deep Learning Explore the basics behindconvolutional neural networks (CNNs)in this MATLAB®Tech Talk. Broadly, convolutional neural networks are a common deep learning architecture – but what exactly is a CNN? This video breaks down this sometimes comp...
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan* & Andrew Zisserman† Visual Geometry Group, Department of Engineering Science, University of Oxford {karen,az}@robots.ox.ac.uk 用于大规模图像识别的深度卷积网络 ...
Convolutional neural networks (ConvNets) are widely used tools for deep learning. They are specifically suitable for images as inputs, although they are also used for other applications such as text, signals, and other continuous responses. They differ from other types of neural networks in a fe...