20 citations · 55 across the 6 of their papers we have counts for
7 papers
AquaCubeAI-Powered Monitoring Turbidity on-board Φsat-2
Pietro Di Stasio, Francesca Razzano, Elisa Liparulo +6
Timely monitoring of coastal water quality is critical for environmental protection, yet conventional satellite workflows rely on downlink and ground processing, introducing latenc…
GEO-Bench-2: From Performance to Capability, Rethinking Evaluation in Geospatial AI
Naomi Simumba, Nils Lehmann, Paolo Fraccaro +9
Geospatial Foundation Models (GeoFMs) are transforming Earth Observation (EO), but evaluation lacks standardized protocols. GEO-Bench-2 addresses this with a comprehensive framewor…
Toward task-driven satellite image super-resolution
Maciej Ziaja, Pawel Kowaleczko, Daniel Kostrzewa +2
Super-resolution is aimed at reconstructing high-resolution images from low-resolution observations. State-of-the-art approaches underpinned with deep learning allow for obtaining…
Unlocking the Use of Raw Multispectral Earth Observation Imagery for Onboard Artificial Intelligence
Gabriele Meoni, Roberto Del Prete, Federico Serva +3
Nowadays, there is growing interest in applying Artificial Intelligence (AI) on board Earth Observation (EO) satellites for time-critical applications, such as natural disaster res…
A Multibranch Convolutional Neural Network for Hyperspectral Unmixing
Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé +2
Hyperspectral unmixing remains one of the most challenging tasks in the analysis of such data. Deep learning has been blooming in the field and proved to outperform other classic u…
Graph Neural Networks Extract High-Resolution Cultivated Land Maps from Sentinel-2 Image Series
Lukasz Tulczyjew, Michal Kawulok, Nicolas Longépé +2
Maintaining farm sustainability through optimizing the agricultural management practices helps build more planet-friendly environment. The emerging satellite missions can acquire m…
Rain regime segmentation of Sentinel-1 observation learning from NEXRAD collocations with Convolution Neural Networks
Aurélien Colin, Pierre Tandeo, Charles Peureux +3
Remote sensing of rainfall events is critical for both operational and scientific needs, including for example weather forecasting, extreme flood mitigation, water cycle monitoring…