在CNN(1)中,我们用到下图来说明卷积之后feature maps尺寸和深度的变化.这一节中,我们讨论feature map size, padding and stride. 首先,在Layer1中,输入是32x32的图片,而卷积之后为28x28,试问filter的size(no padding)? (答案是5x5). 如果没答上来,请看下图: I是一张7x7的图片,filter是3x3的,I*K生成的feature map是5x5的.所以我们推出feature map size公式为: 其…

CNN 大概是目前 CV 界最火爆的一款模型了,堪比当年的 SVM.从 2012 年到现在,CNN 已经广泛应用于CV的各个领域,从最初的 classification,到现在的semantic segmentation, object detection,instance segmentation,super resolution 甚至 optical flow 都能看的其身影.还真是,无所不能. 虽然 CNN 的应用可以说是遍地开花,但是细究起来,可以看到 CNN 的基本模型还是万变不离其宗…

论文题目<Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks> 论文作者:Y ushi Chen, Member , IEEE, Hanlu Jiang, Chunyang Li, Xiuping Jia, Senior Member , IEEE, and Pedram Ghamisi, Member , IEEE 论文发表年份:20…

A Beginner's Guide To Understanding Convolutional Neural Networks Introduction Convolutional neural networks. Sounds like a weird combination of biology and math with a little CS sprinkled in, but these networks have been some of the most influential…

Adit Deshpande CS Undergrad at UCLA ('19) Blog About A Beginner's Guide To Understanding Convolutional Neural Networks Part 2 Introduction Link to Part 1 In this post, we’ll go into a lot more of the specifics of ConvNets. Disclaimer: Now, I do reali…

Adit Deshpande CS Undergrad at UCLA ('19) Blog About A Beginner's Guide To Understanding Convolutional Neural Networks Introduction Convolutional neural networks. Sounds like a weird combination of biology and math with a little CS sprinkled in, but…

An Intuitive Explanation of Convolutional Neural Networks https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/ Posted on August 11, 2016 by ujjwalkarn What are Convolutional Neural Networks and why are they important? Convolutional Neural…

Table of Contents: Architecture Overview ConvNet Layers Convolutional Layer Pooling Layer Normalization Layer Fully-Connected Layer Converting Fully-Connected Layers to Convolutional Layers ConvNet Architectures Layer Patterns Layer Sizing Patterns C…

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications 论文链接:https://arxiv.org/pdf/1704.04861.pdf 摘要和Prior Work就略了,懒:)   Summary: 总的来说,MobileNet相对于标准卷积过程有以下几点不同: 1) 将标准的卷积操作分为两步:depthwise convolution和pointwise convolution.即…

http://cs231n.github.io/   里面有很多相当好的文章 http://cs231n.github.io/convolutional-networks/ Table of Contents: Architecture Overview ConvNet Layers Convolutional Layer Pooling Layer Normalization Layer Fully-Connected Layer Converting Fully-Connected Laye…