Posters

Participation

3 ECTS points are awarded for full participation in the summer school which includes bringing a poster.

Formalities

• Bring a poster. Ideally about work related to geometric deep learning but any topic is welcome. The poster should be no larger than A0 in portrait mode (841 mm wide x 1189 mm tall).
• Pitch your poster before the poster session. The pitch is a 1-minute presentation with 1 or 2 slides. The time limit is strict!
• Present your poster at the poster session.

Poster printing will not be available at the venue. Make sure to print your poster before departure! If you participate online, you do not need to print your poster.

Posters should also be emailed to Patrick Møller Jensen, patmjen@dtu.dk, along with the poster pitch slides, no later than August 6 2021. Posters will appear on this webpage unless otherwise requested. A prize is awarded to the best poster!

Presented Posters

Winner of best poster:

• Marloes E. Arts: Protein Structure Variance Prediction using Deep Learning and Molecular Dynamics Simulations.

Runner ups:

• Max K. Nielsen: Skinning of Puppeteered Characters using MeshCNN and Depth Vision.
• Christian Ingwersen: SparseMeshCNN with Self-Attention for Segmentation of Large Meshes.

All posters:

• Sidsel Borup Winther: Susceptibility-induced fiber orientation dependency of the DWI signal in white matter measured in ex vivo monkey brain at 7 T.
• Kristine Aa. Sørensen: Unsupervised latent space representation of Left Atrial Appendage morphology.
• Andreas Lauritzen: Improving breast cancer risk estimation by combining mammographic texture and AI for lesion detection.
• Mathias Perslev: U-Sleep: resilient high-frequency sleep staging.
• Christian Ingwersen: SparseMeshCNN with Self-Attention for Segmentation of Large Meshes.
• Patrick M. Jensen: Faster Multi-Object Segmentation using Parallel Quadratic Pseudo-Boolean Optimization.
• Malte Pedersen: 3D-ZeF: A 3D Zebrafish Tracking Benchmark Dataset.
• Emil T. S. Kjær: Automated Characterization of the Atomic Structure of Mono-Metallic Nanoparticles from X-ray Scattering Data using Generative Models.
• Rasmus Tuxen: Tensor Factorized Density Estimation.
• Anton Eskildsen: Eye images can be modified to remove iris pattern information while remaining usable for gaze estimation.
• Tareq Abdel Alim: PyCranium: A 3D Photogrammetry Toolbox for Cranial Shape Analysis.
• Joakim B. Haurum: Multi-Scale Hybrid Vision Transformer for Fine-Grained Classification.
• Roberta E. Hunt: Intro to PhD Project: Automated Visual Taxonomic Identification and Clustering of Insects.
• Chenhao Wang: The Computerized Analysis of Mitochondrial Cristae.
• Peidi Xu: Segmentation of 3D jaw images with MultiPlanar UNet.
• Christian K. Eschen: Investigation of Coronary Angiographies of patients with Ischemic Heart Disease using deep learning.
• Arno van Hilten: GenNet Framework: Interpretable Neural Networks for Predicting Phenotype from Genotype.
• Marloes E. Arts: Protein Structure Variance Prediction using Deep Learning and Molecular Dynamics Simulations.
• Xianjing Liu: Geometric Deep Learning for 3D Facial Shape Analysis.
• Josefine V. Sundgaard: Title omitted.
• Max K. Nielsen: Skinning of Puppeteered Characters using MeshCNN and Depth Vision.
• Manja G. Grønberg: Sampling to adjust for imbalance in production data.
• Mathias H. Jensen: Bridge Simulation on Lie Groups and Homogeneous Spaces.
• Tim F. Olsen: Synthesis of Frame Field-Aligned Multi-Laminar Structures.
• Robin Bruneau: 3D Reconstruction of Insects in Amber.
• Abraham G. Smith: Title omitted.
• Lei Li: 3D Lidar Point Cloud Analysis for Biomass Estimation.
• Sepideh Amiri: Pancreas segmentation in abdominal CT scans.
• Jeppe Thagaard: Quantifying Spatial Cellular Distributions.
• Sophia E. Bardenfleth: Vertebra Segmentation using Deep Learning.
• Nora J. Forbes: Radiotherapy induced cardiovascular toxicity: delineating hearts in 8000 patient CT scans.