21 citations · 45 across the 4 of their papers we have counts for
4 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…
Quantum Latent Diffusion Models
Francesca De Falco, Andrea Ceschini, Alessandro Sebastianelli +2
The introduction of quantum concepts is increasingly making its way into generative machine learning models. However, while there are various implementations of quantum Generative…
Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation
Zhitong Xiong, Yi Wang, Fahong Zhang +7
Earth observation (EO) in open-world settings presents a unique challenge: different applications rely on diverse sensor modalities, each with varying ground sampling distances, sp…
Estimating optical vegetation indices and biophysical variables for temperate forests with Sentinel-1 SAR data using machine learning techniques: A case study for Czechia
Daniel Paluba, Bertrand Le Saux, Přemysl Stych
Current optical vegetation indices (VIs) for monitoring forest ecosystems are well established and widely used in various applications, but can be limited by atmospheric effects su…