McDowell CV is a LuaLaTeX class for building neat and space-efficient CVs using the design originally proposed by Gayle L. McDowell athttp://www.careercup.com/resume.
The class is based on article
class. The paper format is set to U.S. letterpaper by default. A template showing an example usage of the class is included.
calibri
- sets calibri as the main font. Otherwise the default font is Times New Roman since version 1.1.0.The class features the following commands:
\name{name}
- defines the applicant's name to be printed by \printheader
.\address{address}
- defines the applicant's address to be printed by \printheader
.\contacts{contacts}
- defines the applicant's contacts to be printed by \printheader
.\makecvheader
- prints the CV header consisting of the name (see the \name
command), address (see the \address
command) and contacts (see the \contacts
command).\begin{cvsection}{sectionname}
- prints a section with a header consisting of the name in bold small caps and a page-wide horizontal line below.\begin{cvsubsection}[linesnum]{left}{center}{right}{content}
- prints a subsection with header consisting of the left
, center
and right
titles. The optional linesnum
argument defines the amount of lines in the header. The argument only affects the vertical spacing between the environment header and content thus eliminating the effect of tabu package vertical spacing bug.lualatex
(see http://www.luatex.org/download.html) is installed on your machine and is available in the terminal or a command line client of your choice.McDowell_CV_Template.tex
and mcdowellcv.cls
, and run the following command: lualatex McDowell_CV_Template.tex
.CV即计算机视觉,简单的来说:计算机模拟人来理解图像所表达的意思,或对图像进行一些理智的操作,比如分割,分类等等。 目前接触到的计算机视觉主要有: 图像分类(包括细粒度特征分类):将图像进行分类,该图像是飞机 ?汽车?狗?或者什么 目标定位和识别(如yolo ssd等神经网络):图像中的目标物体的位置(用框就行标注),框中物体的种类,是什么 图像分割:比如一张CT照片中,要
2. 计算机视觉CV 计算机视觉是指用摄像头和电脑及其他相关设备,对生物视觉的一种模拟 其主要任务是让计算机理解图片或视频中的内容,就像人类和许多其他生物每天所做的那样 2.1 任务目标拆分 让计算机理解图片中的场景 让计算机识别场景中包含的物体 让计算机定位物体在图像中的位置 让计算机理解物体之间的关系或行为 2.2 计算机视觉常见任务 图像分类 将图像结构化为某一类别的信息,用事先确定好的类别
转自:http://hi.baidu.com/rencj/blog/item/0b6d0ef7a1c75a20720eec82.html 众所周知, computer vision(cv) 存在ICCV/CVPR/ECCV三个顶级会议, 它们档次差不多, 都应该在一流会议行列, 没有必要给个高下. 有些us的人认为ICCV/CVPR略好于ECCV,而欧洲人大都认为ICCV/ECCV略好于CVP
CV和ML领域的大牛实验室主页不断更新: CV领域: 1)马毅,主页:http://people.eecs.berkeley.edu/~yima/ 2)朱松纯,主页:http://www.stat.ucla.edu/~sczhu/ 3)何恺明,主页:http://kaiminghe.com/ ML领域: 1)周志华,主页:http://cs.nju.edu.cn/zhouzh/