{"id":14622,"date":"2018-11-27T11:01:15","date_gmt":"2018-11-27T15:01:15","guid":{"rendered":"https:\/\/analytics.ncsu.edu\/?p=14622"},"modified":"2018-11-27T11:01:15","modified_gmt":"2018-11-27T15:01:15","slug":"deep-neural-networks","status":"publish","type":"post","link":"https:\/\/analytics.ncsu.edu\/?p=14622","title":{"rendered":"Deep Neural Networks"},"content":{"rendered":"<p>On November 30th, <a href=\"https:\/\/www.lib.ncsu.edu\/events\/coffee-viz-deep-neural-networks-exploration-and-practical-applications\">Hunt Library&#8217;s Teaching and Visualization Lab<\/a> will host a talk by Dr. Healey on the area of deep learning, with a specific focus on convolutional neural networks (CNNs), a class of deep neural network often used for image analysis. <!--more--><\/p>\n<p>The talk will begin with a very brief overview followed by a more focused discussion of CNNs. Dr. Healey will then present two ongoing projects in his research lab: a method to visualize the internal structure and  response of a CNN to specific inputs or classes of inputs, and a system that can generate content for faces that have significant areas &#8220;removed&#8221; by a grey mask. The face completion can not only generate a unique, photorealistic repair; it can also control properties of the result, for example, whether the individual is smiling of frowning, whether (given sufficient ambiguity in the original, masked image) the individual looks like a male or a female, and so on. The talk will conclude with examples, both positive and negative, of the face completion system. <\/p>\n<p>When:<br \/>\nFriday, November 30, 2018<br \/>\n9:30am to 10:30am <\/p>\n<p>Where:<br \/>\nTeaching and Visualization Lab at the James B. Hunt, Jr. Library<\/p>\n","protected":false},"excerpt":{"rendered":"<p>On November 30th, Hunt Library&#8217;s Teaching and Visualization Lab will host a talk by Dr. Healey on the area of deep learning, with a specific focus on convolutional neural networks (CNNs), a class of deep neural network often used for image analysis.<\/p>\n","protected":false},"author":1,"featured_media":11093,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-14622","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=\/wp\/v2\/posts\/14622","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14622"}],"version-history":[{"count":2,"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=\/wp\/v2\/posts\/14622\/revisions"}],"predecessor-version":[{"id":14624,"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=\/wp\/v2\/posts\/14622\/revisions\/14624"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=\/wp\/v2\/media\/11093"}],"wp:attachment":[{"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14622"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14622"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/analytics.ncsu.edu\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14622"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}