EVOLUTION OF THE COPERNICUS LAND SERVICE PORTFOLIO INTEGRATING NOVEL EO DATA AND LATEST MACHINE LEARNING ALGORITHMS TO CONTINUOUSLY MONITOR THE STATUS, DYNAMICS AND BIOMASS OF THE LAND SURFACE

Informations projet

EVOLAND

N° de convention de subvention: 101082130

DOI

10.3030/101082130

Date de signature de la CE 10 Octobre 2022

Date de début 1 Janvier 2023

Date de fin 31 Decembre 2025

Financé au titre de

• Digital, Industry and Space

Coût total

€ 4 999 531,26

Contribution de l’UE

€ 4 999 531,25

Coordonné par

VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK N.V.
Belgium

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Data Management Plan (1)

Data management plan - interim version

Document describing how to implement the FAIR data principles, as well as data types, licenses and formats used within the project.

Documents, reports (3)

Best practices for running large scale EO processes in the cloud - final version

Report with best practices on algorithm and code design for cloud processing.

Infrastructure requirements report - final version

Report with an inventory of the infrastructure required for operational implementation/ of the next-generation CLMS services, and for the project’s methodological developments and prototypic implementations.

EO missions catalogue relevant for EvoLand - final version

Inventory of available relevant EO data over EvoLand test and prototype sites. D2.1 is complementary to D1.2, but is viewed from the supplier side, while D1.2 covers the demand side.

Websites, patent fillings, videos etc. (1)

Visual identity, project branding and website

Report describing visual elements used in the project as well as the branding materials and website.

Publications

Conference proceedings (1)

DeCUR: decoupling common & unique representations for multimodal self-supervision

Auteurs: Yi Wang, Conrad M Albrecht, Nassim Ait Ali Braham, Chenying Liu, Zhitong Xiong, Xiao Xiang Zhu
Publié dans: 2023
Éditeur: Computer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and P
DOI: 10.48550/arXiv.2309.05300