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	<div class="breadcrumbs"><a href="https://youngmindsonline.org">Home</a> <span class="sep"> / </span> <a href="https://youngmindsonline.org/category/business-innovation/">Business &amp; Innovation</a> <span class="sep"> / </span> <span class="current">Deep-learning algorithm predicts photos’ memorability at ‘near-human’ levels</span></div>			 <article id="post-5166" class="post-5166 post type-post status-publish format-standard has-post-thumbnail hentry category-business-innovation">
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                    <h1 class="entry-title">Deep-learning algorithm predicts photos’ memorability at ‘near-human’ levels</h1>
                                                <aside id="meta-5166" class="entry-meta"><span class="posted-on">Posted on </span><a href="https://youngmindsonline.org/2015/12/23/deep-learning-algorithm-predicts-photos-memorability-near-human-levels/" title="10:40 AM"><time class="entry-date" datetime="2015-12-23T10:40:15+05:30">December 23, 2015</time></a><span class="by-author"> by </span><span class="author vcard"><a class="url fn n" href="https://youngmindsonline.org/author/admin/" title="View all posts by admin" rel="author">admin</a></span><span class="posted-in"> in </span><a href="https://youngmindsonline.org/category/business-innovation/" rel="tag">Business &amp; Innovation</a> 				<span class="with-comments"> with </span>
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					<p>Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a deep-learning algorithm that can predict how memorable or forgettable an image is almost as accurately as humans, and they plan to turn it into an app that tweaks photos to make them more memorable.For each photo, the “MemNet” algorithm also creates a “heat map” (a color-coded overlay) that identifies exactly which parts of the image are most memorable. You can try it out online by uploading your own photos to the project’s “LaMem” dataset.The research is an extension of a similar algorithm the team developed for facial memorability. </p>
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