DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data

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 corr...

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Autores principales:	Chiara Gervasi, Alessia Ferrari, Ioannis Papoutsis, Souzana Touloumtzi
Formato:	article
Lenguaje:	EN IT
Publicado:	mediaGEO soc. coop. 2021
Materias:	Artificial Intelligence Deep learning Machine learning Earth observation Climate change Cartography GA101-1776 Cadastral mapping GA109.5
Acceso en línea:	https://doaj.org/article/ba675035dfab454eaffebd3aeb34e29b
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spelling	oai:doaj.org-article:ba675035dfab454eaffebd3aeb34e29b2021-11-09T17:39:09ZDEEPCUBE: Explainable AI Pipelines for Big Copernicus Data10.48258/geo.v25i3.18021128-81322283-5687https://doaj.org/article/ba675035dfab454eaffebd3aeb34e29b2021-09-01T00:00:00Zhttps://www.mediageo.it/ojs/index.php/GEOmedia/article/view/1802https://doaj.org/toc/1128-8132https://doaj.org/toc/2283-5687 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. Chiara GervasiAlessia FerrariIoannis PapoutsisSouzana TouloumtzimediaGEO soc. coop.articleArtificial IntelligenceDeep learningMachine learningEarth observationClimate changeCartographyGA101-1776Cadastral mappingGA109.5ENITGEOmedia, Vol 25, Iss 3 (2021)
institution	DOAJ
collection	DOAJ
language	EN IT
topic	Artificial Intelligence Deep learning Machine learning Earth observation Climate change Cartography GA101-1776 Cadastral mapping GA109.5
spellingShingle	Artificial Intelligence Deep learning Machine learning Earth observation Climate change Cartography GA101-1776 Cadastral mapping GA109.5 Chiara Gervasi Alessia Ferrari Ioannis Papoutsis Souzana Touloumtzi DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data
description	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.
format	article
author	Chiara Gervasi Alessia Ferrari Ioannis Papoutsis Souzana Touloumtzi
author_facet	Chiara Gervasi Alessia Ferrari Ioannis Papoutsis Souzana Touloumtzi
author_sort	Chiara Gervasi
title	DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data
title_short	DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data
title_full	DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data
title_fullStr	DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data
title_full_unstemmed	DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data
title_sort	deepcube: explainable ai pipelines for big copernicus data
publisher	mediaGEO soc. coop.
publishDate	2021
url	https://doaj.org/article/ba675035dfab454eaffebd3aeb34e29b
work_keys_str_mv	AT chiaragervasi deepcubeexplainableaipipelinesforbigcopernicusdata AT alessiaferrari deepcubeexplainableaipipelinesforbigcopernicusdata AT ioannispapoutsis deepcubeexplainableaipipelinesforbigcopernicusdata AT souzanatouloumtzi deepcubeexplainableaipipelinesforbigcopernicusdata
_version_	1718440958072193024

DEEPCUBE: Explainable AI Pipelines for Big Copernicus Data

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