Projects
Actualiseren van de synthetische randvoorwaarden voor het opstellen van overstromingsgevaarkaarten Flanders Hydraulics
Improving (typo)graphic navigation in contemporary non-linear magazines with large-scale documentation. Reading texts, images, grid systems and their relations, in the era of digitization. Hasselt University
Biomechanical models for predicting the acute and long-term outcome of endovascular repair in patients with type B aortic dissections Ghent University
An aortic dissection is a life threatening cardiovascular disease, characterised by at least one tear in the inner layer of the aortic wall. Due to this tear, blood can enter in the aortic wall and a part of the wall can delaminate, thus separating the blood flow into a false (i.e. abnormal blood path) and true lumen (i.e. normal blood path). One of the common treatments for an aortic dissection is the placement of a stent graft to seal the ...
Reputation and Structural Reforms of Public Organizations: Explaining Temporal Dynamics. University of Antwerp
X-ray reconstruction of foam microstructure formation. University of Antwerp
Novel tools for test evaluation and disease prevalence estimation HOGENT
Designing High-Performing Networks for Multi-Scale Computer Vision KU Leuven
Since the emergence of deep learning, the computer vision field has flourished with models improving at a rapid pace on more and more complex tasks. We distinguish three main ways to improve a computer vision model: (1) improving the data aspect by for example training on a large, more diverse dataset, (2) improving the training aspect by for example designing a better optimizer, and (3) improving the network architecture (or network for ...
International training on epidemiology, biostatistics and qualitative research methods (I-EBQ). University of Antwerp
IVESS: Intelligent Vocabulary and Example Selection for Spanish vocabulary learning. Ghent University
By conducting fundamental research on ICALL-related NLP techniques and applying them to
Spanish, this project aims to contribute to the future architecture of ICALL vocabulary learning.
Additionally, by analysing teachers’ and learners’ attitudes towards data-driven learning, the project
will also provide valuable insights into the applicability of ICALL vocabulary learning in a didactic
setting.