1. 论文思想

将3D卷积分解为spatial convolution in each channel and linear projection across channels.
(spatial convolution + linear projection.)

2. 两种卷积对比

3. 总结

简单概括就是spatial conv + linear projection,但是在spatial conv的时候用了一个residual connection,感觉很有道理,例如是一个vertical edge detector,那么horizontal information将丢失。这个和后来的MobileNet中的depthwise conv + pointwise conv非常的像。

论文笔记——Factorized Convolutional Neural Networks的更多相关文章

  1. 论文笔记(1)-Dropout-Improving neural networks by preventing co-adaptation of feature detectors

    Improving neural networks by preventing co-adaptation of feature detectors 是Hinton在2012年6月份发表的,从这篇文章 ...

  2. 论文笔记:Diffusion-Convolutional Neural Networks (传播-卷积神经网络)

    Diffusion-Convolutional Neural Networks (传播-卷积神经网络)2018-04-09 21:59:02 1. Abstract: 我们提出传播-卷积神经网络(DC ...

  3. 【论文笔记】Progressive Neural Networks 渐进式神经网络

    Progressive NN Progressive NN是第一篇我看到的deepmind做这个问题的.思路就是说我不能忘记第一个任务的网络,同时又能使用第一个任务的网络来做第二个任务. 为了不忘记之 ...

  4. 论文笔记—Flattened convolution neural networks for feedforward acceleration

    1. 论文思想 一维滤过器.将三维卷积分解成三个一维卷积.convolution across channels(lateral), vertical and horizontal direction ...

  5. 深度学习论文翻译解析(十七):MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

    论文标题:MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications 论文作者:Andrew ...

  6. 读convolutional Neural Networks Applied to House Numbers Digit Classification 的收获。

    本文以下内容来自读论文以后认为有价值的地方,论文来自:convolutional Neural Networks Applied to House Numbers Digit Classificati ...

  7. 论文笔记——MobileNets(Efficient Convolutional Neural Networks for Mobile Vision Applications)

    论文地址:MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications MobileNet由Go ...

  8. 《Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks》论文笔记

    论文题目<Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Ne ...

  9. 论文笔记之:Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking

    Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking  arXiv Paper ...

随机推荐

  1. Java实现批量插入

    //方法执行的开始时间 long startTime = System.currentTimeMillis(); Connection conn = null; try{ //获取连接 conn = ...

  2. 抽象语法符号ASN.1(Abstract Syntax Notation One)

      一.ASN.1 (Abstract Syntax Notation One) ASN.1包括两部分:数据描述语言(ISO 8824)和数据编码规则(ISO 8825).ASN.1的数据描述语言允许 ...

  3. JavaScript中通过arguments对象实现对象的重载

    <!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <title> ...

  4. 从MySQL开发规范处看创业

    版权声明:本文为博主原创文章.未经博主同意不得转载. https://blog.csdn.net/n88Lpo/article/details/78099185 作者:唐勇.深圳市环球易购.MySQL ...

  5. 全套 AR 应用设计攻略都在这里!

    版权声明:本文为博主原创文章.未经博主同意不得转载. https://blog.csdn.net/jILRvRTrc/article/details/79823908 通过将虚拟内容与现实世界融合,增 ...

  6. [LeetCode] 42. Trapping Rain Water_hard tag: Two Pointers

    Given n non-negative integers representing an elevation map where the width of each bar is 1, comput ...

  7. 浅谈Java中的初始化和清理

    引言 这篇文章我们主要介绍Java初始化和清理的相关内容,这些内容虽然比较基础,但是还是在这边做一个简单的总结,方便以后查阅. 初始化过程 Java尽力保证:所有变量在使用之前都会得到恰当的初始化(对 ...

  8. 安卓备份 To Do(待办事项)的数据库

    真正路径:/data/data/com.mediatek.todos/databases/todos.db 使用过链接的路径:/data/user/0/com.mediatek.todos/datab ...

  9. [How to] ROOT, Backup & Flash (MTKDroidTools, Spflashtool, CWM)

    这是一篇来自xda论坛的文章,写得很详细,很有用,以下是原文: Hi This is a guide to ROOT, backup and flash your MTK65xx or Other d ...

  10. VCS中的覆盖率分析

    VCS在仿真过程中,也可以收集Coverage Metric.其中覆盖率类型有: 1)Code Coverage:包括control_flow和value两部分的coverage,line_cover ...