7 citations · 12 across the 15 of their papers we have counts for
15 papers
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…
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…
Transformer-Driven Active Transfer Learning for Cross-Hyperspectral Image Classification
Muhammad Ahmad, Francesco Mauro, Manuel Mazzara +3
Hyperspectral image (HSI) classification presents inherent challenges due to high spectral dimensionality, significant domain shifts, and limited availability of labeled data. To a…
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…
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…
From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks
Andrea Ceschini, Francesco Mauro, Francesca De Falco +7
Quantum Graph Neural Networks (QGNNs) represent a novel fusion of quantum computing and Graph Neural Networks (GNNs), aimed at overcoming the computational and scalability challeng…
Quanv4EO: Empowering Earth Observation by means of Quanvolutional Neural Networks
Alessandro Sebastianelli, Francesco Mauro, Giulia Ciabatti +4
A significant amount of remotely sensed data is generated daily by many Earth observation (EO) spaceborne and airborne sensors over different countries of our planet. Different app…
AI techniques for near real-time monitoring of contaminants in coastal waters on board future Phisat-2 mission
Francesca Razzano, Pietro Di Stasio, Francesco Mauro +4
Differently from conventional procedures, the proposed solution advocates for a groundbreaking paradigm in water quality monitoring through the integration of satellite Remote Sens…
QSpeckleFilter: a Quantum Machine Learning approach for SAR speckle filtering
Francesco Mauro, Alessandro Sebastianelli, Maria Pia Del Rosso +2
The use of Synthetic Aperture Radar (SAR) has greatly advanced our capacity for comprehensive Earth monitoring, providing detailed insights into terrestrial surface use and cover r…
A Hybrid MLP-Quantum approach in Graph Convolutional Neural Networks for Oceanic Nino Index (ONI) prediction
Francesco Mauro, Alessandro Sebastianelli, Bertrand Le Saux +2
This paper explores an innovative fusion of Quantum Computing (QC) and Artificial Intelligence (AI) through the development of a Hybrid Quantum Graph Convolutional Neural Network (…
Monitoring water contaminants in coastal areas through ML algorithms leveraging atmospherically corrected Sentinel-2 data
Francesca Razzano, Francesco Mauro, Pietro Di Stasio +4
Monitoring water contaminants is of paramount importance, ensuring public health and environmental well-being. Turbidity, a key parameter, poses a significant problem, affecting wa…
Using Multi-Temporal Sentinel-1 and Sentinel-2 data for water bodies mapping
Luigi Russo, Francesco Mauro, Babak Memar +3
Climate change is intensifying extreme weather events, causing both water scarcity and severe rainfall unpredictability, and posing threats to sustainable development, biodiversity…
Estimation of Ground NO2 Measurements from Sentinel-5P Tropospheric Data through Categorical Boosting
Francesco Mauro, Luigi Russo, Fjoralba Janku +2
This study aims to analyse the Nitrogen Dioxide (NO2) pollution in the Emilia Romagna Region (Northern Italy) during 2019, with the help of satellite retrievals from the Sentinel-5…
A Machine Learning Approach to Long-Term Drought Prediction using Normalized Difference Indices Computed on a Spatiotemporal Dataset
Veronica Wairimu Muriga, Benjamin Rich, Francesco Mauro +2
Climate change and increases in drought conditions affect the lives of many and are closely tied to global agricultural output and livestock production. This research presents a no…
SEN2DWATER: A Novel Multispectral and Multitemporal Dataset and Deep Learning Benchmark for Water Resources Analysis
Francesco Mauro, Benjamin Rich, Veronica Wairimu Muriga +2
Climate change has caused disruption in certain weather patterns, leading to extreme weather events like flooding and drought in different parts of the world. In this paper, we pro…