activity
20242026
collaborators

11 papers

cs.LG2026

Monitoring Post-Disaster Urban Recovery Using High-Resolution SAR Time Series and Unsupervised Learning: Evidence from the 2023 Türkiye-Syria Earthquake

Luigi Russo, Deodato Tapete, Silvia Liberata Ullo +1

Monitoring post-disaster recovery is essential for understanding how urban systems rebuild and progressively return to functionality. However, tracking reconstruction remains diffi…

eess.IV2026

CryoNet: A Deep Learning Framework for Multi-Modal Debris-Covered Glacier Mapping. A Case Study of the Poiqu Basin, Central Himalaya

Farzaneh Barzegar, Tobias Bolch, Norbert Kuehtreiber +1

Glaciers play a critical role as freshwater reserves and indicators of climate change, yet their automatic delineation, especially for debris-covered glaciers, remains challenging…

quant-ph2026

Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learning

Fan Fan, Yilei Shi, Mihai Datcu +5

Machine Learning (ML) has been widely applied across numerous domains due to its ability to automatically identify informative patterns from data for various tasks. The availabilit…

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

An Efficient Machine Learning Framework for Forest Height Estimation from Multi-Polarimetric Multi-Baseline SAR data

Francesca Razzano, Wenyu Yang, Sergio Vitale +3

Accurate forest height estimation is crucial for climate change monitoring and carbon cycle assessment. Synthetic Aperture Radar (SAR), particularly in multi-channel configurations…

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…