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HTTP/1.1 200 OKConnection: keep-aliveContent-Length: 10508Server: GitHub.comContent-Type: text/html; charsetutf-8permissions-policy: interest-cohort()Last-Modified: Fri, 12 Jun 2020 07:35:53 GMTAccess

!DOCTYPE html>html xmlnshttp://www.w3.org/1999/xhtml xml:langzh-Hans langzh-Hans>head>  meta charsetUTF-8 />  title>Automatic Dataset Augmentation/title>  meta namerobots contentall />  meta nameauthor contentYalong Bai>  meta http-equivX-UA-Compatible contentIE100 />  link relstylesheet typetext/css hrefpublic/css/autoset.css />  link relstylesheet typetext/css hrefpublic/css/reset.css />  link relstylesheet typetext/css hrefpublic/css/comment.css />  script>    (function (i, s, o, g, r, a, m) {    iGoogleAnalyticsObject  r; ir  ir || function () {      (ir.q  ir.q || ).push(arguments)    }, ir.l  1 * new Date(); a  s.createElement(o),      m  s.getElementsByTagName(o)0; a.async  1; a.src  g; m.parentNode.insertBefore(a, m)    })(window, document, script, https://www.google-analytics.com/analytics.js, ga);    ga(create, UA-105536234-1, auto);    ga(send, pageview);  /script>  script srcpublic/javascripts/jquery/1.5.2/jquery.min.js>/script>/head>body>  div classoutline>/div>  div classcontainer>    div idcontent>      div classabout>        div classprofile>          div classinfo width100%>            div classfirst-name>Automatic Dataset Augmentation/div>            p classextra-info>An automatically constucted dataset for augmenting ILSVRC-2012 dataset./p>          /div>        /div>        div classmarkdown-body>          div classabout-page>            div classline-2>              h1>Details/h1>              p>AutoDA is constructed to augment existing dataset ILSVRC-2012. The dataset is labeled by both Web and DCNN.                Web provides massive images with rich contextual information, while DCNN well-trained on ILSVRC-2012 are                used to label these images and filter out noisy images. Meanwhile, the rich contextual information from Web                ensures DCNN to achieve high labeling accuracy with relatively low confidence threshold. Together, we can                augment the ILSVRC-2012 dataset in a scalable, accurate, and informative way./p>              p>The AutoDA dataset contai

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