3 citations · 4 across the 9 of their papers we have counts for
5 papers · 1 filter
Exploring Interpretability in Deep Learning-Based Forest Classification - Separating Similar Forest Classes using Sentinel-2 Time Series
Maximilian Kirsch, Christine Preisach
The ecological insurance theory posits that diverse forests are more resilient and better able to adapt to changing environmental conditions. Increasing drought and heat stress in…
Representation Learning of Auxiliary Concepts for Improved Student Modeling and Exercise Recommendation
Yahya Badran, Christine Preisach
Personalized recommendation is a key feature of intelligent tutoring systems, typically relying on accurate models of student knowledge. Knowledge Tracing (KT) models enable this b…
Early Detection of Forest Calamities in Homogeneous Stands -- Deep Learning Applied to Bark-Beetle Outbreaks
Maximilian Kirsch, Jakob Wernicke, Pawan Datta +1
Climate change has increased the vulnerability of forests to insect-related damage, resulting in widespread forest loss in Central Europe and highlighting the need for effective, c…
Sparse Binary Representation Learning for Knowledge Tracing
Yahya Badran, Christine Preisach
Knowledge tracing (KT) models aim to predict students' future performance based on their historical interactions. Most existing KT models rely exclusively on human-defined knowledg…
Supervised Transfer Learning Framework for Fault Diagnosis in Wind Turbines
Kenan Weber, Christine Preisach
Common challenges in fault diagnosis include the lack of labeled data and the need to build models for each domain, resulting in many models that require supervision. Transfer lear…