This study will examine whether the application of hybrid classifiers increases the classification accuracy in comparison to a single classifier. A combination between parametric and non-parametric classifiers will be applied and their performance will be assessed. The student is expected to gain a deep knowledge of applied Machine Learning algorithms within this innovation laboratory.
EAGLE MSc Defense: Active Learning and Parameter-Efficient Feature Adaptation for Cross-City Seismic Building Type Transfer Using DINOv2 and Street-Level Imagery
On November 12, 2026, Christina Krause will present her Master Thesis on " Active Learning and Parameter-Efficient Feature Adaptation for Cross-City Seismic Building Type Transfer Using DINOv2 and Street-Level Imagery" at 14:00 at the EORC Meeting Room (1st floor) in...
![[spotlight] Lecturer Spotlight: Thilo Erbertseder](https://eagle-science.org/wp-content/uploads/2026/10/Thilo_Lecturer_Portrait_EAGLE_EORC_2026-400x250.jpg)
