课程四(Convolutional Neural Networks),第三 周(Object detection) —— 1.Practice questions:Detection algorithms











【解释】
tree的两个bounding boxes 都要保留,因为交并比小于0.5;car 0.73保留;pedestrain 0.98保留;motorcycle 0.58保留。一共5个。

【解释】
5个anchor box, 一个anchor box 对应(1+4+20)个标签,所以output volume 是 19*19*5*25
课程四(Convolutional Neural Networks),第三 周(Object detection) —— 1.Practice questions:Detection algorithms的更多相关文章
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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
- 《java并发编程实战》笔记
<java并发编程实战>这本书配合并发编程网中的并发系列文章一起看,效果会好很多. 并发系列的文章链接为: Java并发性和多线程介绍目录 建议: <java并发编程实战>第 ...
- Java-Selenium,获取下拉框中的每个选项的值,并随机选择某个选项
今天逛51testing,看见有人问这个问题.现在以Select标签为例. 1.首先看页面中的下拉框,如图: 2.F12查看页面源代码,如下 <select class="form-c ...
- @Scheduler与cron
- 【Selenium】【BugList3】firefox与Selenium版本不兼容,报: Message: Unsupported Marionette protocol version 2, required 3
环境信息:Windows7 64位 + python 3.6.5 + selenium 3.11.0 +pyCharm 1 #coding=utf-8 2 from selenium import w ...
- linux 查看内网流量
可以使用iftop进行Linux机器的网络流量监控 安装方法 centos系统下 第一步:安装EPEL源 yum install epel-release 第二部:安装iftop yum instal ...
- (PMP)第13章-----项目相关方管理
13.1 识别相关方 1 相关方分类的方法: 1.1 权力/利益方格,权力/影响方格,影响/作用方格(小型项目,关系简单) 权力:基于相关方的职权级别: 利益:对项目成果的关心程度 影响:对项目成果的 ...
- bzoj4555(多项式求逆解法)
//和以前写的fft不太一样,可能是因为要取模?? #include<iostream> #include<cstring> #include<cmath> #in ...
- 运行第一个Python程序
Python的三种运行方式 交互式解释器 在终端输入python3 进入python交互式解释器 输入exit()退出交互式解释器 命令行脚本 创建python脚本 通过命令执行程序 python h ...
- 阅读笔记4 我是一只IT小小鸟
经过一周连续三四天八小时以上坐在电脑前敲代码的“折磨”,去看看其他经受这些折磨的人的感受.这次读书笔记变成了逗比风,因为前几周认认真真记下书里写的重点内容,然后把学习的内容认真的记录下来的笔记被老师助 ...
- ESP32 windows开发环境的搭建(官方方法)
首先保证电脑中的已经下载了git客户端,没有的自行去https://git-scm.com/下载 STEP1: 获得编译工具链 Windows没有内置的“make”环境,所以安装工具链你将需要一个兼容 ...