Learning Goals:

  • Understand the challenges of Object Localization, Object Detection and Landmark Finding
  • Understand and implement non-max suppression
  • Understand and implement intersection over union
  • Understand how we label a dataset for an object detection application
  • Remember the vocabulary of object detection (landmark, anchor, bounding box, grid, ...)

【中文翻译】

学习目标:

  • 了解对象定位、目标检测和特征点查询的挑战
  • 了解并实现non-max suppression
  • 了解并实现intersection over union
  • 了解如何为对象检测应用程序标记数据集
  • 记住对象检测的词汇表 (landmark、 anchor、bounding box、grid、...)

课程四(Convolutional Neural Networks)，第三 周（Object detection） —— 0.Learning Goals的更多相关文章

  1. 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 ...

  2. 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 ...

  3. 课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） —— 0.Learning Goals

    Learning Goals Understand multiple foundational papers of convolutional neural networks Analyze the ...

  4. 课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） —— 2.Programming assignments : Keras Tutorial - The Happy House (not graded)

    Keras tutorial - the Happy House Welcome to the first assignment of week 2. In this assignment, you ...

  5. 课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） ——3.Programming assignments : Residual Networks

    Residual Networks Welcome to the second assignment of this week! You will learn how to build very de ...

  6. 课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 0.Learning Goals

    Learning Goals Understand the convolution operation Understand the pooling operation Remember the vo ...

  7. 课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） —— 1.Practice questions

    [解释] 应该是same padding 而不是 valid padding . [解释] 卷积操作用的应该是adding additional layers to the network ,而是应该 ...

  8. 课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 1.Practice questions：The basics of ConvNets

    [解释] 100*(300*300*3)+ 100=27000100 [解释] (5*5*3+1)*100=7600 [中文翻译] 您有一个输入是 63x63x16, 并 将他与32个滤波器卷积, 每 ...

  9. 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 ...

  10. 课程四(Convolutional Neural Networks)，第三 周（Object detection） —— 2.Programming assignments：Car detection with YOLOv2

    Autonomous driving - Car detection Welcome to your week 3 programming assignment. You will learn abo ...

随机推荐

  1. 360浏览器对CSS的补齐

    360浏览器对很多CSS不兼容,导致了很多代码显示不正常, 常见的解决方法: 很多人在源代码加了<meta content=\"IE=edge\" http-equiv=\& ...

  2. short s1 = 1; s1 = s1 + 1;和 short s1 = 1; s1 += 1;的问题，终于弄懂了

    对于short s1 = 1; s1 = s1 + 1; 由于s1+1运算时会自动提升表达式的类型,所以结果是int型,再赋值给short类型s1时,编译器将报告需要强制转换类型的错误. 对于shor ...

  3. [leetcode]57. Insert Interval插入区间

    Given a set of non-overlapping intervals, insert a new interval into the intervals (merge if necessa ...

  4. [leetcode]42. Trapping Rain Water雨水积水问题

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

  5. 46-web页面登入前和登入后控制

    可以将user存入session中,然后在前端根据能否取到user,来判断是否登入 <c:if test="${user == null }"> <li clas ...

  6. [原]CentOS7.2部署KVM虚拟机

    前段时间学习了关于PostGis.OSM数据以及Mapnik相关内容,接下来将利用假期重点学习PostgreSQL-XL和瓦片服务器集群技术,因此先把环境搭好.计划采用KVM来充分利用家里不太宽裕的“ ...

  7. cookie和session 以及Django中应用

    cookie和session 以及Django中应用   cookie和session机制 cookie和session机制 cookie机制采用的是在客户端保持状态的方案.作用就是为了解决HTTP协 ...

  8. 正则RegExp的懒惰性和贪婪性; 分组捕获；

    1.正则的懒惰性??? 每次在它的方法exec中捕获的时候,只捕获第一次匹配的内容,而不往下捕获,我们把这种情况称为正则的懒惰性 且每一次捕获的位置都是从索引0开始 正则的实例对象上有一个lastin ...

  9. 记一次Django报错Reverse for 'indextwo' with no arguments not found. 1 pattern(s) tried: ['$index/$']

    启动python manage.py runserver 打开127.0.0.1:8000,报错信息如下: Reverse for 'indextwo' with no arguments not f ...

  10. [字符串]TrBBnsformBBtion

    TrBBnsformBBtion Let us consider the following operations on a string consisting of A and B: Select ...