30 citations · 42 across the 7 of their papers we have counts for
11 papers
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…
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…
AMD-HookNet for Glacier Front Segmentation
Fei Wu, Nora Gourmelon, Thorsten Seehaus +4
Knowledge on changes in glacier calving front positions is important for assessing the status of glaciers. Remote sensing imagery provides the ideal database for monitoring calving…
Pixel-wise Distance Regression for Glacier Calving Front Detection and Segmentation
Amirabbas Davari, Christoph Baller, Thorsten Seehaus +3
Glacier calving front position (CFP) is an important glaciological variable. Traditionally, delineating the CFPs has been carried out manually, which was subjective, tedious and ex…
On Mathews Correlation Coefficient and Improved Distance Map Loss for Automatic Glacier Calving Front Segmentation in SAR Imagery
Amirabbas Davari, Saahil Islam, Thorsten Seehaus +3
The vast majority of the outlet glaciers and ice streams of the polar ice sheets end in the ocean. Ice mass loss via calving of the glaciers into the ocean has increased over the l…
Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm
Rosanna Dietrich-Sussner, Amirabbas Davari, Thorsten Seehaus +4
Supervised machine learning requires a large amount of labeled data to achieve proper test results. However, generating accurately labeled segmentation maps on remote sensing image…
Glacier Calving Front Segmentation Using Attention U-Net
Michael Holzmann, Amirabbas Davari, Thorsten Seehaus +3
An essential climate variable to determine the tidewater glacier status is the location of the calving front position and the separation of seasonal variability from long-term tren…
Bayesian U-Net for Segmenting Glaciers in SAR Imagery
Andreas Hartmann, Amirabbas Davari, Thorsten Seehaus +3
Fluctuations of the glacier calving front have an important influence over the ice flow of whole glacier systems. It is therefore important to precisely monitor the position of the…