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Programme

September 5

12:00-13:00 Registration (with light lunch)

Session 1 - 13:00-17:00 - Health IT and General ML
13:00-13:05 - Brief intro remarks
13:05-13:50 - Invited talk: Chiranjib Bhattacharyya "The need for Depth in Deep Learning Architectures: Using Inherent structures to understand depth of RBMs"
13:50-14:15 - Chenjie Ge, Irene Gu, Asgeir Jakola and Jie Yang “Brain tumor classification using slice-based deep learning and fusion of multi-modal MR images”
14:15-14:45 - Coffee break
14:45-15:45 - Poster session
15:45-16:30 - Invited talk: Hossein Azizpour "Deep Learning in Life Science"
16:30-17:00 - Elisabeth Wetzer, Joakim Lindblad, Ida-Maria Sintorn, Kjell Hultenby and Natasa Sladoje “Towards automated multiscale imaging and analysis in TEM: Glomeruli detection by fusion of CNN and LBP maps”

September 6
Session 2 - 9:00 - 12:00 - NLP
9:00-9:45 - Invited talk: Chris Dyer "Designing Deep Models for Improved Generalization"
9:45-10:15 - Olof Mogren and Richard Johansson “Character-based recurrent neural networks for morphological relational reasoning”
10:15-10:45 - Coffee break
10:45-11:30 - Invited talk: Joakim Nivre "Deep Learning for Natural Language Processing – A Rabbit's Perspective"
11:30-12:00 - Raphaela Heil, Ekta Vats and Anders Hast “Exploring the Applicability of Capsule Networks for Word Spotting in Historical Handwritten Manuscripts”

12:00-13:00 - Lunch break

Session 3 - 13:00 - 17:00 - Vision
13:00-13:45 - Invited talk: Christian Igel "Deep learning: Some tricks of the trade"
13:45-14:15 - Kalyan Ram Ayyalasomayajula, Filip Malmberg and Anders Brun “Realistic handwritten document generation using an RNN with style transfer based pre- and post-processing”
14:15-14:45 - Adam Nyberg, David Bergström, Henrik Petersson and David Gustafsson “Transforming Thermal Images to Visible Spectrum Images using Deep Learning”
14:45-15:15 - Coffee break
15:15-16:00 - Invited talk: Atsuto Maki "Feature Contraction: New ConvNet Regularization in Image Classification"
16:00-16:30 - Erik Valldor, K-G Stenborg and David Gustafsson “Firearm Detection in Social Media Images”
16:30-17:00 - Martin Längkvist and Amy Loutfi “Learning Representations for Image Manipulation and Predictive Effects from Language Actions”
17:00-17:05 - Brief concluding remarks
 

 

The list of accepted papers is shown below:

Chenjie Ge, Irene Gu, Asgeir Jakola and Jie Yang “Brain tumor classification using slice-based deep learning and fusion of multi-modal MR images”
Chenjie Ge, Qixun Qu, Irene Gu and Asgeir Jakola “Alzheimer's Disease Detection Using 3D Multiscale Convolutional Networks and Feature Fusion”
Claes Lundström “Analytic Imaging Diagnostics Arena – national synergies for AI in medical imaging”
Adam Nyberg, David Bergström, Henrik Petersson and David Gustafsson “Transforming Thermal Images to Visible Spectrum Images using Deep Learning”
Erik Valldor, K-G Stenborg and David Gustafsson “Firearm Detection in Social Media Images”
Martin Längkvist and Amy Loutfi “Learning Representations for Image Manipulation and Predictive Effects from Language Actions”
Tim Olsson, Belén Luque and Alessandro Pieropan “Improving 6DOF object pose estimation using a novel data generation method”
Richard Johansson “Multi-treebank Syntactic Parsing via Multitask Learning”
Ali Basirat “Word Embedding through PCA”
John Martinsson, Alexander Schliep, Björn Eliasson, Christian Meijner, Simon Persson and Olof Mogren “Automatic blood glucose prediction with confidence using recurrent neural networks”
Olof Mogren and Richard Johansson “Character-based recurrent neural networks for morphological relational reasoning”
Elisabeth Wetzer, Joakim Lindblad, Ida-Maria Sintorn, Kjell Hultenby and Natasa Sladoje “Towards automated multiscale imaging and analysis in TEM: Glomeruli detection by fusion of CNN and LBP maps”
Raphaela Heil, Ekta Vats and Anders Hast “Exploring the Applicability of Capsule Networks for Word Spotting in Historical Handwritten Manuscripts”
Eva Breznik, Filip Malmberg, Joel Kullberg, Håkan Ahlström and Robin Strand “Using deep learning with anatomical information for segmentation of abdominal organs in whole-body MRI”
Kalyan Ram Ayyalasomayajula, Filip Malmberg and Anders Brun “Realistic handwritten document generation using an RNN with style transfer based pre- and post-processing”
Mikael Kågebäck, Devdatt Dubhashi and Asad Sayeed “DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning”

Page Manager: Webbredaktionen|Last update: 9/3/2018
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