Learning Goals

  • Understand multiple foundational papers of convolutional neural networks
  • Analyze the dimensionality reduction of a volume in a very deep network
  • Understand and Implement a Residual network
  • Build a deep neural network using Keras
  • Implement a skip-connection in your network
  • Clone a repository from github and use transfer learning

学习目标

　　卷积神经网络多基础论文的理解
　　在非常深的网络中分析体积的降维
　　了解并实施剩余网络
　　利用 Keras 构建深神经网络
　　在网络中实现skip-connection
　　从 github 克隆一个仓库并使用转移学习

 

课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） —— 0.Learning Goals的更多相关文章

  1. Convolutional Neural Networks: Step by Step

    Andrew Ng deeplearning courese-4:Convolutional Neural Network Convolutional Neural Networks: Step by ...

  2. Convolutional Neural Networks: Application

    Andrew Ng deeplearning courese-4:Convolutional Neural Network Convolutional Neural Networks: Step by ...

  3. 课程四(Convolutional Neural Networks)，第四 周（Special applications: Face recognition & Neural style transfer） —— 2.Programming assignments：Art generation with Neural Style Transfer

    Deep Learning & Art: Neural Style Transfer Welcome to the second assignment of this week. In thi ...

  4. 课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 3.Programming assignments：Convolutional Model: application

    Convolutional Neural Networks: Application Welcome to Course 4's second assignment! In this notebook ...

  5. 课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 2.Programming assignments：Convolutional Model: step by step

    Convolutional Neural Networks: Step by Step Welcome to Course 4's first assignment! In this assignme ...

  6. [C4W2] Convolutional Neural Networks - Deep convolutional models: case studies

    第二周 深度卷积网络:实例探究(Deep convolutional models: case studies) 为什么要进行实例探究?(Why look at case studies?) 这周我们 ...

  7. ImageNet Classification with Deep Convolutional Neural Networks（译文）转载

    ImageNet Classification with Deep Convolutional Neural Networks Alex Krizhevsky, Ilya Sutskever, Geo ...

  8. AlexNet论文翻译-ImageNet Classification with Deep Convolutional Neural Networks

    ImageNet Classification with Deep Convolutional Neural Networks 深度卷积神经网络的ImageNet分类 Alex Krizhevsky ...

  9. 中文版 ImageNet Classification with Deep Convolutional Neural Networks

    ImageNet Classification with Deep Convolutional Neural Networks 摘要 我们训练了一个大型深度卷积神经网络来将ImageNet LSVRC ...

随机推荐

  1. php面试题五之nginx如何调用php和php-fpm的作用和工作原理

    nginx如何调用php 采用nginx+php作为webserver的架构模式,在现如今运用相当广泛.然而第一步需要实现的是如何让nginx正确的调用php.由于nginx调用php并不是如同调用一 ...

  2. 随笔 | 分布式版本控制系统Git的安装与使用

    作业要求来自https://edu.cnblogs.com/campus/gzcc/GZCC-16SE2/homework/2097 GitHub远程仓库的地址https://github.com/W ...

  3. adb pull 文件夹到电脑

    正常来讲是支持文件夹的. 但实际执行的时候发现: pull: building file list...0 files pulled. 0 files skipped. 其实出现这个提示,归根到底还是 ...

  4. HDU 6214.Smallest Minimum Cut 最少边数最小割

    Smallest Minimum Cut Time Limit: 2000/2000 MS (Java/Others)    Memory Limit: 65535/32768 K (Java/Oth ...

  5. Json中对日期的处理

    前言:Json对日期的处理很特别,我们不能简单的转换而得到我们想要的结果,需要进行特殊处理 一.JSon序列化和反序列化对日期的处理 JsonHelper类: using System.IO; usi ...

  6. ABP框架系列之三：(Entity Framework Integration-实体框架集成)

    ASP.NET Boilerplate can work with any O/RM framework. It has built-in integration with EntityFramewo ...

  7. 获得文件的CRC32值

    使用方法:先调用init_crc32_tab生成查询表,再调用calc_img_crc获得文件的CRC值. #define Poly 0xEDB88320L//CRC32标准 ];//CRC查询表 / ...

  8. Spring mvc解决url传递中文参数乱码问题

    在tomcat服务器中,修改server.xml参数,如<Connector URIEncoding="UTF-8" connectionTimeout="2000 ...

  9. python_day1_程序交互

    程序交互 在编写程序过程中总会有程序与用户交互的场景出现,这里面提到python会使用一个方法:input 用法: 例如:请用户输入一个账号 input"Please input your ...

  10. Paper | Contrast Limited Adaptive Histogram Equalization

    目录 1. 背景 1.1. 对比度和直方图均衡HE 1.2. HE的问题 1.3. AHE 1.4. 底噪问题 2. CLAHE 2.1. 效果展示 2.2. 算法格式和细节 论文:Contrast ...