A GNN-Based Architecture for Group Detection from Spatio-Temporal Trajectory Data

Detecting and analyzing group behavior from spatio-temporal trajectories is an interesting topic in various domains, such as autonomous driving, urban computing, and social sciences. This paper revisits the group detection problem from spatio-temporal trajectories and proposes “WavenetNRI”, a graph neural network (GNN) based method. The...

Spatio-temporal prediction of missing temperature with stochastic Poisson equations: The LC2019 team winning entry for the EVA 2019 data competition

This paper presents our winning entry for the EVA 2019 data competition, the aim of which is to predict Red Sea surface temperature extremes over space and time. To achieve this, we used a stochastic partial differential equation (Poisson equation) based method, improved through a regularization to penalize large magnitudes of solutions. This...

Using a Space Filling Curve for the Management of Dynamic Point Cloud Data in a Relational DBMS

The rapid developments in the field of point cloud acquisition technologies have allowed point clouds to become an important source of information for many applications. One of the newest applications of point clouds concerns the monitoring of the coast. Many countries, among which the Netherlands, use this source of data in order to determine...