3 citations · 4 across the 4 of their papers we have counts for
7 papers
Scaling Laws for Geospatial Foundation Models: A case study on PhilEO Bench
Nikolaos Dionelis, Riccardo Musto, Jente Bosmans +7
Foundation Models (FMs) have achieved state-of-the-art performance across domains by leveraging large-scale pretraining. In Earth Observation (EO), the availability of petabyte-sca…
CARE: Confidence-Aware Regression Estimation of building density fine-tuning EO Foundation Models
Nikolaos Dionelis, Jente Bosmans, Nicolas Longépé
Performing accurate confidence quantification and assessment in pixel-wise regression tasks, which are downstream applications of AI Foundation Models for Earth Observation (EO), i…
TerraMesh: A Planetary Mosaic of Multimodal Earth Observation Data
Benedikt Blumenstiel, Paolo Fraccaro, Valerio Marsocci +8
Large-scale foundation models in Earth Observation can learn versatile, label-efficient representations by leveraging massive amounts of unlabeled data. However, existing public da…
Building Age Estimation: A New Multi-Modal Benchmark Dataset and Community Challenge
Nikolaos Dionelis, Alessandra Feliciotti, Mattia Marconcini +8
Estimating the construction year of buildings is critical for advancing sustainability, as older structures often lack energy-efficient features. Sustainable urban planning relies…
Enhancing Maritime Situational Awareness through End-to-End Onboard Raw Data Analysis
Roberto Del Prete, Manuel Salvoldi, Domenico Barretta +5
Satellite-based onboard data processing is crucial for time-sensitive applications requiring timely and efficient rapid response. Advances in edge artificial intelligence are shift…
Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting
Brandon Victor, Mathilde Letard, Peter Naylor +4
Floods are among the most common and devastating natural hazards, imposing immense costs on our society and economy due to their disastrous consequences. Recent progress in weather…