6 papers
From Machine Learning to Large-Scale EO Products: Best Practices for Making Maps
Ghjulia Sialelli, Robin Young, Yuchang Jiang +9
Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by advances in machine learning (…
DiffVAS: Diffusion-Guided Visual Active Search in Partially Observable Environments
Anindya Sarkar, Srikumar Sastry, Aleksis Pirinen +2
Visual active search (VAS) has been introduced as a modeling framework that leverages visual cues to direct aerial (e.g., UAV-based) exploration and pinpoint areas of interest with…
Grazing Detection using Deep Learning and Sentinel-2 Time Series Data
Aleksis Pirinen, Delia Fano Yela, Smita Chakraborty +1
Grazing shapes both agricultural production and biodiversity, yet scalable monitoring of where grazing occurs remains limited. We study seasonal grazing detection from Sentinel-2 L…
GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
Anindya Sarkar, Srikumar Sastry, Aleksis Pirinen +3
We consider the task of active geo-localization (AGL) in which an agent uses a sequence of visual cues observed during aerial navigation to find a target specified through multiple…
Flexible SE(2) graph neural networks with applications to PDE surrogates
Maria BÃ¥nkestad, Olof Mogren, Aleksis Pirinen
This paper presents a novel approach for constructing graph neural networks equivariant to 2D rotations and translations and leveraging them as PDE surrogates on non-gridded domain…
Impacts of Color and Texture Distortions on Earth Observation Data in Deep Learning
Martin Willbo, Aleksis Pirinen, John Martinsson +3
Land cover classification and change detection are two important applications of remote sensing and Earth observation (EO) that have benefited greatly from the advances of deep lea…