{"id":212,"date":"2014-08-05T12:40:11","date_gmt":"2014-08-05T11:40:11","guid":{"rendered":"http:\/\/deep-learning.compute.dtu.dk\/?page_id=212"},"modified":"2014-08-22T19:42:28","modified_gmt":"2014-08-22T18:42:28","slug":"posters","status":"publish","type":"page","link":"http:\/\/deep-learning.compute.dtu.dk\/?page_id=212","title":{"rendered":"Posters"},"content":{"rendered":"<h6>Gallery<\/h6>\n<ul>\n<li><a style=\"font-size: 16px; font-weight: bold; line-height: 1.5;\" href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Naesseth.pdf\">(winner poster award) SMC methods for graphical models &#8211; Christian Naesseth<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Wilm.pdf\">Real time pose estimation using stereo vision and mapping -Jakob Wilm\u00a0<\/a><\/li>\n<li><a style=\"line-height: 1.5;\" href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Andreasen.pdf\">MRI-only based radiotherapy creating a pseudo CT scan from a T1-weighted MRI scan &#8211; Daniel Andreasen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Jenniches.pdf\">Data mining: Bayesian networks in quantum chromodynamics &#8211; Laura Jenniches<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Kjer.pdf\">Shape modelling of the inner ear from micro-CT data &#8211; Hans Martin\u00a0Kjer<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Kasenburg.pdf\">Brain connectivity change with age &#8211; Niklas Kasenburg<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Keshavarz.pdf\">Sparse modeling of chemical compounds &#8211; Babak Keshavarz<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Puonti.pdf\">Lesion detection using conditional restricted Boltzmann machines &#8211; Oula Puonti<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Pai.pdf\">Image registration using stationary velocity fields parameterized by norm-minimizing Wendland \u00a0kernel &#8211; Akshay Pai<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Jensen.pdf\">Quantitative evaluation of peptide analogue distribution in mouse tissue using 3D computer modelling &#8211; Casper Jensen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Nobel_Joergensen.pdf\">Interactive 3D topology optimization &#8211; Morten Nobel-J\u00f8rgensen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Brost.pdf\">Persistent homology for query performance prediction &#8211; Brian\u00a0Brost<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Madsen.pdf\">Modeling temporal structure in music for emotion prediction using pairwise comparisons &#8211; Jens Madsen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Olsen.pdf\">Model-based motion tracking of infants &#8211; Mikkel Olsen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_vanTulder.pdf\">Discriminative feature learning with restricted\u00a0Boltzmann machines for lung tissue classification &#8211; Gijs\u00a0van Tulder<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Thomsen.pdf\">Identifying visual structures for predicting action affordances &#8211; Mikkel Thomsen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Fischer.pdf\">How to center restricted Botzmann machines &#8211; Asja Fischer<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Olesen.pdf\">Non-invasive estimation of pressure gradients in pulsatile flow using ultrasound &#8211; Jacob Olesen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Moshavegh.pdf\">Automated hierarchical time gain compensation for ultrasound imaging &#8211; Ramin Moshavegh<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Bach_Andersen.pdf\">A diagnostic and predictive framework for wind turbine drive train monitoring &#8211; Martin \u00a0Bach-Andersen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Einarsson.pdf\">A general sampling scheme for LGM&#8217;s with an application to extreme precipitation in Iceland &#8211; Gu\u00f0mundur\u00a0Einarsson<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_abll.pdf\">Measuring particle statistics\u00a0using a CNN-based segmentation &#8211; Anders B. L. Larsen<\/a><\/li>\n<li><a href=\"http:\/\/deep-learning.compute.dtu.dk\/wp-content\/uploads\/2014\/08\/poster_Diao.pdf\">Unsupervised deep learning applied to image segmentation and mammographic risk scoring &#8211; Pengfei Diao<\/a><\/li>\n<\/ul>\n<p><span style=\"font-weight: bold; line-height: 1.5;\">Instructions<\/span><\/p>\n<p>Participation in the summer school will give you 3.0 ECTS credits if you present a poster at the summer school. This includes:<\/p>\n<ul>\n<li>Bringing a poster (relevant to the summer school topic, preferably). Max. dimensions are 88cm wide x 126cm tall (A0 portrait).<\/li>\n<li>A poster teaser (1-2 slides, 1 minute) at the summer school.<\/li>\n<li>Presenting your poster at a designated poster session.<\/li>\n<\/ul>\n<p>Please send an email to michiel.k@di.ku.dk\u00a0with the\u00a0poster\u00a0title,\u00a0your\u00a0poster\u00a0(PDF format)\u00a0and\u00a01-2 teaser slides\u00a0(PDF format)\u00a0no later than 11 August (please include &#8220;poster summer school&#8221; in the subject).\u00a0The poster will be put here and the poster teasers will be compiled and made ready for the summer school.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Gallery (winner poster award) SMC methods for graphical models &#8211; Christian Naesseth Real time pose estimation using stereo vision and mapping -Jakob Wilm\u00a0 MRI-only based radiotherapy creating a pseudo CT scan from a T1-weighted MRI scan &#8211; Daniel Andreasen Data mining: Bayesian networks in quantum chromodynamics &#8211; Laura Jenniches Shape modelling of the inner ear &hellip; <a href=\"http:\/\/deep-learning.compute.dtu.dk\/?page_id=212\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Posters<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":6,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"page-templates\/full-width.php","meta":{"footnotes":""},"class_list":["post-212","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=\/wp\/v2\/pages\/212","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=212"}],"version-history":[{"count":28,"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=\/wp\/v2\/pages\/212\/revisions"}],"predecessor-version":[{"id":367,"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=\/wp\/v2\/pages\/212\/revisions\/367"}],"wp:attachment":[{"href":"http:\/\/deep-learning.compute.dtu.dk\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=212"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}