activity
20192021
most citedA New Mask R-CNN Based Method for Improved Landslide Detection

9 citations · 9 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2021

On Board Volcanic Eruption Detection through CNNs and Satellite Multispectral Imagery

Maria Pia Del Rosso, Alessandro Sebastianelli, Dario Spiller +2

In recent years, the growth of Machine Learning (ML) algorithms has raised the number of studies including their applicability in a variety of different scenarios. Among all, one o…

quant-ph2021

Advantages and Bottlenecks of Quantum Machine Learning for Remote Sensing

Daniela A. Zaidenberg, Alessandro Sebastianelli, Dario Spiller +2

This concept paper aims to provide a brief outline of quantum computers, explore existing methods of quantum image classification techniques, so focusing on remote sensing applicat…

cs.CY2020

AIRSENSE-TO-ACT: A Concept Paper for COVID-19 Countermeasures based on Artificial Intelligence algorithms and multi-sources Data Processing

A. Sebastianelli, F. Mauro, G. Di Cosmo +3

Aim of this paper is the description of a new tool to support institutions in the implementation of targeted countermeasures, based on quantitative and multi-scale elements, for th…

cs.CV20209 cited

A New Mask R-CNN Based Method for Improved Landslide Detection

Silvia Liberata Ullo, Amrita Mohan, Alessandro Sebastianelli +4

This paper presents a novel method of landslide detection by exploiting the Mask R-CNN capability of identifying an object layout by using a pixel-based segmentation, along with tr…

eess.IV2020

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…

eess.IV2020

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…