5 papers
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…
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…
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…
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…
SSL4SAR: Self-Supervised Learning for Glacier Calving Front Extraction from SAR Imagery
Nora Gourmelon, Marcel Dreier, Martin Mayr +5
Glaciers are losing ice mass at unprecedented rates, increasing the need for accurate, year-round monitoring to understand frontal ablation, particularly the factors driving the ca…