{"id":21,"date":"2016-01-08T13:43:52","date_gmt":"2016-01-08T13:43:52","guid":{"rendered":"http:\/\/semisupervised-learning.compute.dtu.dk\/?page_id=21"},"modified":"2016-08-08T11:53:23","modified_gmt":"2016-08-08T11:53:23","slug":"posters","status":"publish","type":"page","link":"http:\/\/semisupervised-learning.compute.dtu.dk\/?page_id=21","title":{"rendered":"Posters"},"content":{"rendered":"

Submitted Posters<\/strong><\/p>\n

    \n
  1. “Towards Autonomous Plant Production using Fully Convolutional Neural Networks<\/a>”
    \n– by Peter Chrstiansen, Aarhus University
    \n(see teaser     here<\/a>)<\/li>\n
  2. “Assessment of Small Bowel Motility with Dynamic MRI<\/a>”
    \n– by\u00a0Esben Bolvig Mark, Aalborg University Hospital
    \n(see teaser     here<\/a>)<\/li>\n
  3. “Image segmentation of x-ray microtomography\u00a0of highly porous media – a work in progress<\/a>”
    \n– by\u00a0Jacob Daniel Kirstejn Hansen, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n
  4. “SimpleElastix: A user-friendly, multi-lingual library for medical image registration<\/a>”
    \n– by Kasper Marstal, Erasmus Medical Center Rotterdam
    \n(see teaser     here<\/a>)<\/li>\n
  5. “Regression on Manifolds<\/a>”
    \n– by Line K\u00fchnel, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n
  6. “Simultaneous brain tumor and organs-at-risk segmentation for radiotherapy<\/a>”
    \n– by\u00a0Mikael Agn, Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  7. “3D Methods of Security X-rayScreening<\/a>”
    \n– by\u00a0Mina Kheirabadi,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  8. “Identifying patient group characteristics using hospital diagnosis records<\/a>”
    \n– by Niels Dalum Hansen, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n
  9. “Travelling Optical Scanner – Casse Study on Brazilian Skulls<\/a>”
    \n– by Dolores Messer,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  10. “Merged 3D volume of optic nerve head using transfinite interpolation<\/a>”
    \n– by Anne-Sofie W.\u00a0Lindberg,\u00a0Technical University of Denmark
    \n(see teasere     here<\/a>)<\/li>\n
  11. “Auxiliary Deep Generative Models<\/a>”
    \n– by\u00a0Lars Maal\u00f8e,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  12. “Investigating Machine Learning for Monte-Carlo noise removal in rendered images<\/a>”
    \n– by\u00a0Andrea Luongo,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  13. “Conv. Network for Segmentation of Mixed Crops<\/a>”
    \n– by\u00a0Anders Krogh Mortensen, Aarhus University
    \n(see teaser     here<\/a>)<\/span><\/li>\n
  14. “Door Recognition and Handle Detection Using Convolutional Neural Nets<\/a>”
    \n– by\u00a0Adrian Llopart Maurin,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  15. “Segmentation of Human Semen using Convolutional Neural Networks<\/a>”
    \n– by Malte S. Nissen, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n
  16. “Strain Mapping in HRTEM Images<\/a>”
    \n– by Jacob Madsen,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  17. “Smartphone-based monitoring and treatment of unipolar and bipolar disorder<\/a>”
    \n– by Jonas Busk,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  18. “Probabilistic model based iterative CT<\/a>”
    \n– by\u00a0Jonathan Scharff Nielsen,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  19. “Multi-phase Image Segmentation with the Adaptive Deformable Mesh<\/a>”
    \n– by Tuan T. Nguyen,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  20. “Correcting a Confused Classifier<\/a>”
    \n– by Kristoffer Stensbo-Smidt, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n
  21. “Active Detection from Adaptive Representation of High Resolution Images<\/a>”
    \n– by Mathieu Laroze, IRISA-UBS and WIPSEA
    \n(see teaser     here<\/a>)<\/span><\/li>\n
  22. “Detection of Prostate Cancer on mpMRI Using Intensity, Gradient and Histogram Features<\/a>”
    \n– by Carina Jensen, Aalborg University Hospital
    \n(see teaser     here<\/a>)<\/li>\n
  23. “Interactive Texture GUI for semi-supervised feature detection<\/a>”
    \n– by Monica J. Emerson
    \n(see teaser     here<\/a>)<\/li>\n
  24. “A special limited-angle tomographic problem<\/a>”
    \n– by Leise Borg, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n
  25. “RADIOGENOMICS learning GENOMIC CLASSES based on IMAGE FEATURES<\/a>”
    \n– by\u00a0Esther Alberts, Technische\u00a0Universit\u00e4t M\u00fcnchen
    \n(see teaser     here<\/a>)<\/li>\n
  26. “Multiple Hypothesis Tracking Based Extraction of Airway Trees from CT Data<\/a>”
    \n– by Raghavendra Selvan, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n
  27. “Inferring behavioural changes from smartphones<\/a>”
    \n– by\u00a0Simon Kamronn, Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  28. “Semi-supervised Sparse LDA<\/a>”
    \n– by\u00a0Gudmundur Einarsson,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  29. “An upcoming Study: Semi-Supervised Learning in EEG-Based Epileptiform Pattern Detection<\/a>”
    \n– by Sirin W. Gangstad, HypoSafe A\/S, Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  30. “Objective Colonoscopy Evaluation”
    \n– by David Norsk,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  31. “Measuring BRDFs with multipurpose hardware”
    \n– by Rasmus A. Lyngby,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  32. “Designing for Color In Additive Manufacturing”
    \n– by Eybor R\u00fanar Eir\u00edksson, Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  33. “A Method for Digitizing Scenes with Complex Objects”
    \n– by Jonathan Dyssel Stets,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  34. “Deep Learning for Invoice Information Extraction”
    \n– by Rasmus Berg Palm,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  35. “A probabilistic model for segmenting EEG into microstates<\/a>”
    \n– by\u00a0Frans Zdyb,\u00a0Technical University of Denmark
    \n(see teaser     here<\/a>)<\/li>\n
  36. “Locally Orderless Registration for Diffusion Weighted Images<\/a>”
    \n– by Henrik Gr\u00f8nholt Jensen, University of Copenhagen
    \n(see teaser     here<\/a>)<\/li>\n<\/ol>\n

    Instructions<\/strong><\/p>\n

    Full 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