21 citations · 21 across the 1 of their papers we have counts for
7 papers
Meta-Learning for Few-Shot Land Cover Classification
Marc Rußwurm, Sherrie Wang, Marco Körner +1
The representations of the Earth's surface vary from one geographic region to another. For instance, the appearance of urban areas differs between continents, and seasonality influ…
Self-attention for raw optical Satellite Time Series Classification
Marc Rußwurm, Marco Körner
The amount of available Earth observation data has increased dramatically in the recent years. Efficiently making use of the entire body information is a current challenge in remot…
Early Classification for Agricultural Monitoring from Satellite Time Series
Marc Rußwurm, Romain Tavenard, Sébastien Lefèvre +1
In this work, we introduce a recently developed early classification mechanism to satellite-based agricultural monitoring. It augments existing classification models by an addition…
BreizhCrops: A Time Series Dataset for Crop Type Mapping
Marc Rußwurm, Charlotte Pelletier, Maximilian Zollner +2
We present Breizhcrops, a novel benchmark dataset for the supervised classification of field crops from satellite time series. We aggregated label data and Sentinel-2 top-of-atmosp…
MultiNet: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery
Tim G. J. Rudner, Marc Rußwurm, Jakub Fil +4
We propose a novel approach for rapid segmentation of flooded buildings by fusing multiresolution, multisensor, and multitemporal satellite imagery in a convolutional neural networ…
Convolutional LSTMs for Cloud-Robust Segmentation of Remote Sensing Imagery
Marc Rußwurm, Marco Körner
Clouds frequently cover the Earth's surface and pose an omnipresent challenge to optical Earth observation methods. The vast majority of remote sensing approaches either selectivel…