<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Computer-Vision on Karpoke - Just Another Blog</title><link>http://karpoke.ignaciocano.com/tags/computer-vision/</link><description>Recent content in Computer-Vision on Karpoke - Just Another Blog</description><generator>Hugo -- 0.167.0</generator><language>es</language><lastBuildDate>Wed, 29 Jun 2016 01:33:00 +0100</lastBuildDate><atom:link href="http://karpoke.ignaciocano.com/tags/computer-vision/index.xml" rel="self" type="application/rss+xml"/><item><title>How We Teach Computers to Understand Pictures</title><link>http://karpoke.ignaciocano.com/2016/06/29/how-we-teach-computers-to-understand-pictures/</link><pubDate>Wed, 29 Jun 2016 01:33:00 +0100</pubDate><guid>http://karpoke.ignaciocano.com/2016/06/29/how-we-teach-computers-to-understand-pictures/</guid><description>&lt;blockquote&gt;
&lt;p&gt;When a very young child looks at a picture, she can identify simple elements:
”cat,” ”book,” ”chair.” Now, computers are getting smart enough to do that
too. What’s next? In a thrilling talk, computer vision expert Fei-Fei Li
describes the state of the art — including the database of 15 million photos
her team built to ”teach” a computer to understand pictures — and the key
insights yet to come.&lt;/p&gt;
&lt;/blockquote&gt;</description></item></channel></rss>