Preserving data privacy in Machine Learning pipelines with Federated Learning

FAME's project blog
Pablo Gil Pereira
Raquel Lazcano
Juan Manuel Vera Diaz
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.

Earth Observation Data Mining: A use case for Forest Monitoring

et al,
José Lorenzo Mon
Paper in the IEEE Geoscience and Remote Sensing Society (IGARSS) 2019 Conference

Artificial Intelligence Data Science Methodology for Earth Observation

et al,
José Lorenzo Mon
Chapter in Book "Advanced Analytics and Artificial Intelligence Applications", 978-1-78984-639-3, by IntechOpen

Data Science Workflows for the CANDELA Project

et al,
José Lorenzo Mon
Publication in Conference proceedings/Workshop “Big Data from Space” (BiDS’19), Munich, Germany, 19-21 February 2019. ISBN 978-92-76-00034-1 ISSN 1831-9424 doi: 10.2760/848593