Marc Conrad Russwurm

Cette personne n’est plus à l’EPFL

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Publications associées (19)

Large-scale detection of marine debris in coastal areas with Sentinel-2

Devis Tuia, Marc Conrad Russwurm

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Here, remote sensing can provide reliable estimates of plastic pollution by regularly monitoring and d ...

2023

Improved marine debris detection in satellite imagery with automatic refinement of coarse hand annotations

Devis Tuia, Marc Conrad Russwurm, Elif Dilge Gül

Plastic litter is a major environmental hazard that endangers human, animal, and plant health on the planet. A substantial portion of plastic pollutants is washed from rivers and beaches into the oceans and aggregates at the surface as marine debris before ...

2023

Meteor: Meta-learning connecting earth problems observed from space

Devis Tuia, Benjamin Alexander Kellenberger, Marc Conrad Russwurm

Satellite remote sensing has become a key technology for monitoring Earth and the processes occurring at its surface. It relies on state-of-the-art machine learning models that require large annotated datasets to capture the extreme diversity of the proble ...

2023

Classification of Tropical Deforestation Drivers with Machine Learning and Satellite Image Time Series

Devis Tuia, Jan Pisl, Marc Conrad Russwurm, Lloyd Haydn Hughes

Tropical deforestation is a major environmental problem with severe consequences such as carbon emissions or biodiversity loss. While much research focuses on monitoring and mapping deforestation, less attention is paid to understanding the various reasons ...

The Institute of Electrical and Electronics Engineers, Inc.2023

Improving Few-Shot Object Detection with Object Part Proposals

Devis Tuia, Marc Conrad Russwurm, Arthur Chevalley

Few-Shot Object Detection (FSOD) allows fast adaptation of an object detection model to new classes of objects using few examples per class. This has many applications, in particular in satellite and aerial observation, as it allows learning from experts w ...

The Institute of Electrical and Electronics Engineers, Inc2023

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Devis Tuia, Marc Conrad Russwurm, Lloyd Haydn Hughes, Oleg Antropov, Sudipan Saha

In this study, we examine the potential of several self-supervised deep learning models in predicting forest attributes and detecting forest changes using ESA Sentinel-1 and Sentinel-2 images. The performance of the proposed deep learning models is compare ...

The Institute of Electrical and Electronics Engineers, Inc2023

Mapping forest cover dynamics in the Swiss Alps using 70 years of aerial imagery

Devis Tuia, Thiên-Anh Claris Nguyen, Benjamin Alexander Kellenberger, Marc Conrad Russwurm

2023

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Devis Tuia, Marc Conrad Russwurm

Learning to predict accurately from a few data samples is a central challenge in modern data-hungry machine learning. On natural images, human vision typically outperforms deep learning approaches on few-shot learning. However, we hypothesize that aerial a ...

IEEE2022

Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer

Marc Conrad Russwurm

Data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGr ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

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