<?xml version="1.0"?>
<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Jeff Running</author_name><author_url>https://www.microsoft.com/en-us/research/people/jeffrunn/</author_url><title>Visual Recognition - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="pdRKsgynPt"&gt;&lt;a href="https://www.microsoft.com/en-us/research/video/visual-recognition/"&gt;Visual Recognition&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/video/visual-recognition/embed/#?secret=pdRKsgynPt" width="600" height="338" title="&#x201C;Visual Recognition&#x201D; &#x2014; Microsoft Research" data-secret="pdRKsgynPt" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
/* &lt;![CDATA[ */
/*! This file is auto-generated */
!function(d,l){"use strict";l.querySelector&amp;&amp;d.addEventListener&amp;&amp;"undefined"!=typeof URL&amp;&amp;(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&amp;&amp;!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i&lt;o.length;i++)o[i].style.display="none";for(i=0;i&lt;a.length;i++)s=a[i],e.source===s.contentWindow&amp;&amp;(s.removeAttribute("style"),"height"===t.message?(1e3&lt;(r=parseInt(t.value,10))?r=1e3:~~r&lt;200&amp;&amp;(r=200),s.height=r):"link"===t.message&amp;&amp;(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&amp;&amp;n.host===r.host&amp;&amp;l.activeElement===s&amp;&amp;(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r&lt;s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document);
//# sourceURL=https://www.microsoft.com/en-us/research/wp-includes/js/wp-embed.min.js
/* ]]&gt; */
&lt;/script&gt;
</html><thumbnail_url>https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/visual-recognition-1.jpg</thumbnail_url><thumbnail_width>640</thumbnail_width><thumbnail_height>480</thumbnail_height><description>The fields of Computer Vision and Machine Learning are becoming increasingly intertwined, with many of the recent breakthroughs in object and scene recognition coming from the availability of large labeled datasets and sophisticated machine learning techniques. In this session of the 2013 Microsoft Research Faculty Summit, leading researchers in these fields share their perspectives on [&hellip;]</description></oembed>
