collaborators

7 papers

cs.LG2026

Parameter-Efficient Domain Adaptation of Physics-Informed Self-Attention based GNNs for AC Power Flow Prediction

Redwanul Karim, Changhun Kim, Timon Conrad +7

Accurate AC power flow (AC-PF) prediction under domain shift is critical when models trained on medium-voltage (MV) grids are deployed on high-voltage (HV) networks. Existing physi…

cs.CV2026

Comparison Study: Glacier Calving Front Delineation in Synthetic Aperture Radar Images With Deep Learning

Nora Gourmelon, Konrad Heidler, Erik Loebel +12

Continuous monitoring of glacier calving fronts is essential for sea level rise projections. This study benchmarks Deep Learning systems for front delineation in Synthetic Aperture…

cs.CV2026

Few-Shot Domain Adaptation with Temporal References and Static Priors for Glacier Calving Front Delineation

Marcel Dreier, Nora Gourmelon, Dakota Pyles +4

During benchmarking, the state-of-the-art model for glacier calving front delineation achieves near-human performance. However, when applied in a real-world setting at a novel stud…

cs.CV2025

AMD-HookNet++: Evolution of AMD-HookNet with Hybrid CNN-Transformer Feature Enhancement for Glacier Calving Front Segmentation

Fei Wu, Marcel Dreier, Nora Gourmelon +6

The dynamics of glaciers and ice shelf fronts significantly impact the mass balance of ice sheets and coastal sea levels. To effectively monitor glacier conditions, it is crucial t…

cs.CV2025

EcoScapes: LLM-Powered Advice for Crafting Sustainable Cities

Martin Röhn, Nora Gourmelon, Vincent Christlein

Climate adaptation is vital for the sustainability and sometimes the mere survival of our urban areas. However, small cities often struggle with limited personnel resources and int…

cs.CV2025

Multi-temporal Calving Front Segmentation

Marcel Dreier, Nora Gourmelon, Dakota Pyles +5

The calving fronts of marine-terminating glaciers undergo constant changes. These changes significantly affect the glacier's mass and dynamics, demanding continuous monitoring. To…