papers
Publications (3)
cs.LG2024
Time-Series Foundation Models for Forecasting Soil Moisture Levels in Smart Agriculture
Boje Deforce, Bart Baesens, EstefanÃa Serral Asensio
The recent surge in foundation models for natural language processing and computer vision has fueled innovation across various domains. Inspired by this progress, we explore the po…
cs.LG2025
End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection
Boje Deforce, Meng-Chieh Lee, Bart Baesens +3
Time series anomaly detection (TSAD) finds many applications such as monitoring environmental sensors, industry KPIs, patient biomarkers, etc. A two-fold challenge for TSAD is a ve…
cs.LG2023
Self-Supervised Anomaly Detection of Rogue Soil Moisture Sensors
Boje Deforce, Bart Baesens, Jan Diels +1
IoT data is a central element in the successful digital transformation of agriculture. However, IoT data comes with its own set of challenges. E.g., the risk of data contamination…