DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data

Autori

  • Chiara Gervasi TRE Altamira
  • Alessia Ferrari TRE Altamira
  • Ioannis Papoutsis National Observatory of Athens
  • Souzana Touloumtzi National Observatory of Athens

Parole chiave:

Artificial Intelligence, Deep learning, Machine learning, Earth observation, Climate change

Abstract

DeepCube is a 3-year Horizon 2020 project that leverages advances in the fields of Artificial Intelligence and Semantic Web to unlock the potential of big Copernicus data. Its goal is to address problems of high socio-environmental impact and enhance our understanding of Earth's processes correlated with Climate Change. To achieve this, the project employs mature ICT technologies, integrating them into a scalable, open and interoperable platform that provides solutions for all phases of an Earth Observation based AI pipeline. The Deep-
Cube technologies will be demonstrated in five Use Cases.

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Pubblicato

2021-09-15

Come citare

Gervasi, C., Ferrari, A., Papoutsis, I., & Touloumtzi, S. (2021). DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data. GEOmedia, 25(3). Recuperato da https://ojs.mediageo.it/index.php/GEOmedia/article/view/1802

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Sezione

REPORT