3 citations · 8 across the 5 of their papers we have counts for
5 papers
An Interpretable Deep Semantic Segmentation Method for Earth Observation
Ziyang Zhang, Plamen Angelov, Eduardo Soares +2
Earth observation is fundamental for a range of human activities including flood response as it offers vital information to decision makers. Semantic segmentation plays a key role…
Self-supervised learning -- A way to minimize time and effort for precision agriculture?
Michael L. Marszalek, Bertrand Le Saux, Pierre-Philippe Mathieu +2
Machine learning, satellites or local sensors are key factors for a sustainable and resource-saving optimisation of agriculture and proved its values for the management of agricult…
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…
Paradigm selection for Data Fusion of SAR and Multispectral Sentinel data applied to Land-Cover Classification
Alessandro Sebastianelli, Maria Pia Del Rosso, Pierre Philippe Mathieu +1
Data fusion is a well-known technique, becoming more and more popular in the Artificial Intelligence for Earth Observation (AI4EO) domain mainly due to its ability of reinforcing A…
Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical Model
Alessandro Sebastianelli, Artur Nowakowski, Erika Puglisi +5
Cloud removal is a relevant topic in Remote Sensing as it fosters the usability of high-resolution optical images for Earth monitoring and study. Related techniques have been analy…