9 citations · 26 across the 6 of their papers we have counts for
3 papers · 1 filter
Time-Series Foundation Models for Forecasting Soil Moisture Levels in Smart Agriculture
Boje Deforce, Bart Baesens, Estefanía 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…
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…
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…