15 citations · 50 across the 27 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
On Circuit-based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification
Alessandro Sebastianelli, Daniela A. Zaidenberg, Dario Spiller +2
This article aims to investigate how circuit-based hybrid Quantum Convolutional Neural Networks (QCNNs) can be successfully employed as image classifiers in the context of remote s…
Automatic Dataset Builder for Machine Learning Applications to Satellite Imagery
Alessandro Sebastianelli, Maria Pia Del Rosso, Silvia Liberata Ullo
Nowadays the use of Machine Learning (ML) algorithms is spreading in the field of Remote Sensing, with applications ranging from detection and classification of land use and monito…
Application of DInSAR Technique to High Coherence Satellite Images for Strategic Infrastructure Monitoring
Tony De Corso, Luca Mignone, Alessandro Sebastianelli +6
In this paper the authors present and validate a procedure, which intends to combine the latest state of the art models in bridge monitoring with freely available satellite data. T…
Landslide Geohazard Assessment With Convolutional Neural Networks Using Sentinel-2 Imagery Data
Silvia L. Ullo, Maximillian S. Langenkamp, Tuomas P. Oikarinen +4
In this paper, the authors aim to combine the latest state of the art models in image recognition with the best publicly available satellite images to create a system for landslide…