{"version":"1.0","provider_name":"2021 Summit","provider_url":"https:\/\/embeddedvisionsummit.com\/2021","title":"A Highly Data-Efficient Deep Learning Approach - 2021 Summit","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"oojgGnEneN\"><a href=\"https:\/\/embeddedvisionsummit.com\/2021\/session\/a-highly-data-efficient-deep-learning-approach\/\">A Highly Data-Efficient Deep Learning Approach<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/embeddedvisionsummit.com\/2021\/session\/a-highly-data-efficient-deep-learning-approach\/embed\/#?secret=oojgGnEneN\" width=\"600\" height=\"338\" title=\"&#8220;A Highly Data-Efficient Deep Learning Approach&#8221; &#8212; 2021 Summit\" data-secret=\"oojgGnEneN\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^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<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(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<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);\n\/\/# sourceURL=https:\/\/embeddedvisionsummit.com\/2021\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/embeddedvisionsummit.com\/2021\/wp-content\/uploads\/sites\/9\/2021\/04\/SpeakerCard_BangertP.jpeg","thumbnail_width":1200,"thumbnail_height":628,"description":"Many applications, such as medical imaging, lack the large amounts of data required for training popular CNNs to achieve sufficient accuracy. Often, these same applications suffer from an imbalanced class distribution problem that negatively impacts model accuracy. In this talk, [&hellip;]"}