activity
20242026
collaborators

8 papers

cs.CV2026

Volcanic Clouds Detection through QCNN and Geostationary Satellite Multispectral Imagery

Federica Torrisi, Claudia Corradino, Alessandro Grilli +5

Recent advances in quantum computing are opening new possibilities for Earth Observation (EO) data analysis. Quantum machine learning (QML) approaches offer novel ways to process i…

quant-ph2025

Enriching Earth Observation labeled data with Quantum Conditioned Diffusion Models

Francesco Mauro, Francesca De Falco, Lorenzo Papa +5

The rapid adoption of diffusion models (DMs) in the Earth Observation (EO) domain has unlocked new generative capabilities aimed at producing new samples, whose statistical propert…

cs.CV2025

A Quantum-assisted Attention U-Net for Building Segmentation over Tunis using Sentinel-1 Data

Luigi Russo, Francesco Mauro, Babak Memar +3

Building segmentation in urban areas is essential in fields such as urban planning, disaster response, and population mapping. Yet accurately segmenting buildings in dense urban re…

quant-ph2025

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…

cs.CV2024

Benchmarking of a new data splitting method on volcanic eruption data

Simona Reale, Pietro Di Stasio, Francesco Mauro +3

In this paper, a novel method for data splitting is presented: an iterative procedure divides the input dataset of volcanic eruption, chosen as the proposed use case, into two part…

eess.IV2024

SEN12-WATER: A New Dataset for Hydrological Applications and its Benchmarking

Luigi Russo, Francesco Mauro, Alessandro Sebastianelli +2

Climate change and increasing droughts pose significant challenges to water resource management around the world. These problems lead to severe water shortages that threaten ecosys…