{"id":2885,"date":"2012-12-20T10:26:38","date_gmt":"2012-12-20T08:26:38","guid":{"rendered":"http:\/\/www.foerderverein-technische-fakultaet.at\/?p=2885"},"modified":"2013-05-03T10:26:48","modified_gmt":"2013-05-03T08:26:48","slug":"ruckblick-machine-learning-for-objective-qoe-assessment-science-myths-and-a-look-to-the-future-slides","status":"publish","type":"post","link":"https:\/\/www.ftf.or.at\/?p=2885","title":{"rendered":"R\u00fcckblick: Machine Learning for objective QoE assessment: Science, Myths and a look to the future [Slides]"},"content":{"rendered":"<p>Der R\u00fcckblick zum TEWI-Kolloquium von\u00a0<strong>Judith Redi, TU Delft<\/strong>\u00a0am\u00a0<a title=\"Colloquium on Quality of Experience in Multimedia Systems and Services\" href=\"http:\/\/www.foerderverein-technische-fakultaet.at\/2012\/11\/colloquium-on-quality-of-experience-in-multimedia-systems-and-services\/\">23.11.2012<\/a>\u00a0beinhaltet die Folien:<\/p>\n<p><iframe loading=\"lazy\" src=\"http:\/\/www.slideshare.net\/slideshow\/embed_code\/15622084\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" width=\"476\" height=\"400\"><\/iframe><\/p>\n<p><strong>Abstract<\/strong>: Machine learning has been recently shown to be a very promising tool to support automated QoE assessment. Its ability to mimic highly non-linear, complex phenomena, such as user experience and quality judgment, is extremely appealing for the implementation of on-line, accurate QoE control systems. Nevertheless, applying Machine Learning to QoE is an high risk, high gain approach: if misused, it can lead to poorly flexible and unreliable systems. Key to the attainment of all the gain without risks is a profound understanding of the advantages and limitations that characterize learning machines. Even more important is a strong knowledge of the phenomenon to be mimicked, that is, the user experience.<br \/>\nIn this talk, theoretical background, applicative tips and practical examples will be reviewed, with the aim of drawing guidelines for the successful application of Machine Learning to objective QoE assessment.<\/p>\n<p><strong>CV<\/strong>: Judith Redi is Assistant Professor at Delft University of Technology, department of Intelligent Systems, since 2010. She obtained her PhD from the University of Genoa (Italy) in 2010, with a thesis on learning machines for objective image quality assessment, final result of a project on <\/p>\n<div style=\"display: none\"><a href='http:\/\/buylevitraaonline.com\/' title='buy levitra online without prescription'>buy levitra online without prescription<\/a><\/div>\n<p> visual quality in displays funded by Philips research. After receiving the award for the best ICT thesis from University of Genoa, she worked as a Post-Doc at Eurecom (France) focusing on image analysis and computer vision. At TU Delft, she works on image and video understanding towards the maximization of the quality of multimedia experiences, for which she was awarded an NWO Veni grant in 2012. She is coordinator of the Qualinet (COST IC1003) Industrial Forum and Management Committee member for the Qualinet COST action.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Der R\u00fcckblick zum TEWI-Kolloquium von\u00a0Judith Redi, TU Delft\u00a0am\u00a023.11.2012\u00a0beinhaltet die Folien: Abstract: Machine learning has been recently shown to be a very promising tool to support automated QoE assessment. Its ability to mimic highly non-linear, complex phenomena, such as user experience &hellip; <a href=\"https:\/\/www.ftf.or.at\/?p=2885\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"sfsi_plus_gutenberg_text_before_share":"","sfsi_plus_gutenberg_show_text_before_share":"","sfsi_plus_gutenberg_icon_type":"","sfsi_plus_gutenberg_icon_alignemt":"","sfsi_plus_gutenburg_max_per_row":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-2885","post","type-post","status-publish","format-standard","hentry","category-tewi-kolloquium"],"_links":{"self":[{"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=\/wp\/v2\/posts\/2885","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2885"}],"version-history":[{"count":4,"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=\/wp\/v2\/posts\/2885\/revisions"}],"predecessor-version":[{"id":4248,"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=\/wp\/v2\/posts\/2885\/revisions\/4248"}],"wp:attachment":[{"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2885"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2885"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ftf.or.at\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2885"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}