| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Dahl, Anders Bjorholm
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (18/18 displayed)
- 2023Elucidating the Bulk Morphology of Cellulose-Based Conducting Aerogels with X-Ray Microtomography
- 2023Elucidating the Bulk Morphology of Cellulose-Based Conducting Aerogels with X-Ray Microtomography
- 2022SparseMeshCNN with Self-Attention for Segmentation of Large Meshescitations
- 2021Quantifying effects of manufacturing methods on fiber orientation in unidirectional composites using structure tensor analysiscitations
- 2020Characterization of the fiber orientations in non-crimp glass fiber reinforced composites using structure tensorcitations
- 2019Process characterization for molding of paper bottles using computed tomography and structure tensor analysis
- 2017Individual fibre segmentation from 3D X-ray computed tomography for characterising the fibre orientation in unidirectional composite materialscitations
- 2017Graphite nodules in fatigue-tested cast iron characterized in 2D and 3Dcitations
- 2015Dictionary Based Segmentation in Volumescitations
- 2015Characterization of boundary roughness of two cube grains in partly recrystallized coppercitations
- 2015Boundary Fractal Analysis of Two Cube-oriented Grains in Partly Recrystallized Coppercitations
- 2014Surface Detection using Round Cutcitations
- 2014Pattern recognition approach to quantify the atomic structure of graphenecitations
- 2014Structure Identification in High-Resolution Transmission Electron Microscopic Imagescitations
- 2014Characterization of graphite nodules in thick-walled ductile cast iron
- 2014Quantification Tools for Analyzing Tomograms of Energy Materials
- 2013Automated Structure Detection in HRTEM Images: An Example with Graphene
- 2012Large scale tracking of stem cells using sparse coding and coupled graphs
Places of action
| Organizations | Location | People |
|---|
document
Surface Detection using Round Cut
Abstract
We propose an iterative method for detecting closed surfaces in a volumetric data, where an optimal search is performed in a graph build upon a triangular mesh. Our approach is based on previous techniques for detecting an optimal terrain-like or tubular surface employing a regular grid.Unlike similar adaptations for triangle meshes, our method is capable of capturing complex geometries by iteratively refining the surface, where we obtain a high level of robustness by applying explicit mesh processing to intermediate results. Our method uses on-surface data support, but it also exploits data information about the region inside and outside the surface. This provides additional robustness to the algorithm.We demonstrate the capabilities of the approach by detecting surfaces of CT scanned objects.