most citedAn experimental study of existing tools for outlier detection and cleaning in trajectories

8 citations · 8 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2025

Federated Learning and Trajectory Compression for Enhanced AIS Coverage

Thomas Gräupl, Andreas Reisenbauer, Marcel Hecko +6

This paper presents the VesselEdge system, which leverages federated learning and bandwidth-constrained trajectory compression to enhance maritime situational awareness by extendin…

cs.AI2025

Building a Foundation Model for Trajectory from Scratch

Gaspard Merten, Mahmoud Sakr, Gilles Dejaegere

Foundation models are transformative in artificial intelligence, but building them from scratch, especially for mobility trajectories, is not yet clear or documented. This tutorial…

cs.DB20258 cited

An experimental study of existing tools for outlier detection and cleaning in trajectories

Mariana M Garcez Duarte, Mahmoud Sakr

Outlier detection and cleaning are essential steps in data preprocessing to ensure the integrity and validity of data analyses. This paper focuses on outlier points within individu…

cs.DB2025

Mobility Stream Processing on NebulaStream and MEOS

Mariana M. Garcez Duarte, Dwi P. A. Nugroho, Georges Tod +7

The increasing use of Internet-of-Things (IoT) sensors in moving objects has resulted in vast amounts of spatiotemporal streaming data. To analyze this data in situ, real-time spat…

cs.HC2025

GeoPandas-AI: A Smart Class Bringing LLM as Stateful AI Code Assistant

Gaspard Merten, Gilles Dejaegere, Mahmoud Sakr

Geospatial data analysis plays a crucial role in tackling intricate societal challenges such as urban planning and climate modeling. However, employing tools like GeoPandas, a prom…

cs.LG2025

Using LLMs for Analyzing AIS Data

Gaspard Merten, Gilles Dejaegere, Mahmoud Sakr

Recent research in Large Language Models (LLMs), has had a profound impact across various fields, including mobility data science. This paper explores the and experiment with diffe…