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<html xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>DLPR 2018</title>
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<link rel="stylesheet" type="text/css" href="css/mystyle.css" <script src="http://cdn.static.runoob.com/libs/jquery/2.1.1/jquery.min.js">
</script>
</head>
<body>
<div class="container">
<!-- <div class="jumbotron">
<div class="content">
</div>
</div> -->
<!-- <div id="head" style="background-color:floralwhite"> -->
<div id="head">
<hr />
<h1 style="text-align:center"><b>The Second International Workshop on
<br> Deep Learning for Pattern Recognition (DLPR2018)</b></h1>
<p style="font-family:'Trebuchet MS', 'Lucida Sans Unicode', 'Lucida Grande', 'Lucida Sans', Arial, sans-serif;
text-align:center">
<i>To be held in conjunction with the 24th International Conference on Pattern Recognition ICPR 2018, August 20th,
2018. Beijing, China</i> </p>
<img src="DLPR_logo2.jpg" class="img-responsive" alt="Cinque Terre">
</div>
<div class="row">
<div class="span6 offset2">
<ul class="nav nav-tabs">
<li class="active">
<a href="index.html">Home</a>
</li>
<!-- <li> <a href="dataset.html">Dataset</a></li> -->
<!-- <li><a href="tasks.html">Tasks</a></li> -->
<li>
<a href="Organizers.html">Organization Committee</a>
</li>
<li>
<a href="Important Dates.html">Important Dates</a>
</li>
<li>
<a href="Invited Speakers.html">Invited Speakers</a>
</li>
<li>
<a href="Submission.html">Submission</a>
</li>
<!-- <li>
<a href="Registration.html">Registration</a>
</li> -->
<li>
<a href="Program.html">Program</a>
</li>
<li>
<a href="Contact.html">Contact</a>
</li>
<br />
</ul>
</div>
</div>
<div class="row">
<div class="span12">
<!-- <h2 style="color:darkblue">Call For Papers</h2> -->
<br>
<p>
Deep Learning, which can be treated as the most significant breakthrough in the past 10 years in the field of pattern recognition and machine learning, has greatly affected the methodology of related fields like computer vision and achieved terrific progress in both academy and industry. It can be seen as a resolution to change the whole pattern recognition system. It achieved an end-to-end pattern recognition, merging the previous steps of pre-processing, feature extraction, classifier design and post-processing. It is expected that the development of deep learning theories and applications would further influence the field of pattern recognition. The major goal of this workshop is to provide a platform for researchers or graduate students around the world to report or exchange their progresses on deep learning for pattern recognition.
</p>
<h2>News</h2>
<p>
<ul>
<li>Call for Paper is announced here!</li>
</ul>
</p>
<h2 style="color:darkblue">Important dates</h3>
<ul class="">
<li>Paper Submissions: <strong>June 1, 2018</strong></li>
<li>Author Notification: <strong>June 30, 2018</strong></li>
<li>Camera ready dealine: <strong>July 15, 2018</strong></li>
<li>Workshop Date: <strong>August 20, 2018</strong></li>
</ul>
<h2 style="color:darkblue">Scope and Topics</h3>
<div style="padding-left: 2em">
<p>
<ur>
<li><span style="font-size: 16px"><span >Deep learning architectures for pattern recognition</span></span></li>
<li><span style="font-size: 16px"><span >Optimization for deep learning</span></span></li>
<li><span style="font-size: 16px"><span >Sparse coding in deep learning</span></span></li>
<li><span style="font-size: 16px"><span >Transfer learning for deep learning</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for feature representation</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for facial analysis</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for object recognition</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for scene understanding</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for document analysis</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for dimension reduction</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for activity recognition</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for semantic segmentation</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for generative modeling</span></span></li>
<li><span style="font-size: 16px"><span >Deep learning for biometrics</span></span></li>
<li><span style="font-size: 16px"><span >Multi-modal deep learning</span></span></li>
<li><span style="font-size: 16px"><span >Performance evaluation of deep learning algorithms</span></span></li>
</ur>
</p>
</div>
<br>
</div>
</div>
</div>
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