196 citations · 258 across the 8 of their papers we have counts for
8 papers
SHAZAM: Self-Supervised Change Monitoring for Hazard Detection and Mapping
Samuel Garske, Konrad Heidler, Bradley Evans +2
The increasing frequency of environmental hazards due to climate change underscores the urgent need for effective monitoring systems. Current approaches either rely on expensive la…
Machine Learning for Methane Detection and Quantification from Space - A survey
Enno Tiemann, Shanyu Zhou, Alexander Kläser +3
Methane () is a potent anthropogenic greenhouse gas, contributing 86 times more to global warming than Carbon Dioxide () over 20 years, and it also acts as an air pollu…
On the Foundations of Earth and Climate Foundation Models
Xiao Xiang Zhu, Zhitong Xiong, Yi Wang +7
Foundation models have enormous potential in advancing Earth and climate sciences, however, current approaches may not be optimal as they focus on a few basic features of a desirab…
PixelDINO: Semi-Supervised Semantic Segmentation for Detecting Permafrost Disturbances
Konrad Heidler, Ingmar Nitze, Guido Grosse +1
Arctic Permafrost is facing significant changes due to global climate change. As these regions are largely inaccessible, remote sensing plays a crucial rule in better understanding…
A Deep Active Contour Model for Delineating Glacier Calving Fronts
Konrad Heidler, Lichao Mou, Erik Loebel +3
Choosing how to encode a real-world problem as a machine learning task is an important design decision in machine learning. The task of glacier calving front modeling has often bee…
Self-supervised Audiovisual Representation Learning for Remote Sensing Data
Konrad Heidler, Lichao Mou, Di Hu +5
Many current deep learning approaches make extensive use of backbone networks pre-trained on large datasets like ImageNet, which are then fine-tuned to perform a certain task. In r…
Aerial Scene Understanding in The Wild: Multi-Scene Recognition via Prototype-based Memory Networks
Yuansheng Hua, Lichao Moua, Jianzhe Lin +2
Aerial scene recognition is a fundamental visual task and has attracted an increasing research interest in the last few years. Most of current researches mainly deploy efforts to c…
HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline
Konrad Heidler, Lichao Mou, Celia Baumhoer +2
Deep learning-based coastline detection algorithms have begun to outshine traditional statistical methods in recent years. However, they are usually trained only as single-purpose…