Artificial Intelligence for the European Open Science Cloud

Informations projet

AI4EOSC

N° de convention de subvention: 101058593

DOI

10.3030/101058593

Projet clôturé

Date de signature de la CE 11 Mai 2022

Date de début 1 Septembre 2022

Date de fin 31 Août 2025

Financé au titre de

• Research infrastructures

Coût total

€ 4 997 125,00

Contribution de l’UE

€ 4 997 125,00

Coordonné par

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Spain

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

Documents, reports (9)

Communication, training, outreach, dissemination and collaboration/liaison and exploitation plans

This document will contain the plans for all dissemination communication collaboration and collaborationliaison activities exploitation including the basic metrics to measure the viability of the presented plan

WP4 Implementation plan

This document describes the implementation plan for the first implementation and integration phase

Initial plan for Quality Assurance and data FAIRness

Definition and plan of the Software Services and Applications Quality Assurance and the automatic assessment of data FAIRness Plan of infrastructure for the services Software and application development

Data Management Plan

Will define the project DMP as expected in the GA

Updated Communication, training, outreach, dissemination and collaboration/ liaison and exploitation plans and results

This document will contain an update and review of D21

Implementation plan

This document describes the implementation plan for the first implementation and integration phase

State of the art landscaping and initial platform requirements specification

This document provides an overview of the most relevant technologies available together with the key requirements of the AI platform and the codesign approach employed

Initial high-level architecture specification

This document provides the first architecture specification of the AI platform

Analysis of user applications, collection of requirements

This deliverable can be combined with D31 State of the art landscaping and initial platform requirements and provides a prioritised list of user requirements and the implementation roadmap

Publications

Peer reviewed articles (14)

Detecting district heating leaks in thermal imagery: Comparison of anomaly detection methods

Auteurs: Vollmer, Elena; Ruck, Julian; Volk, Rebekka; Schultmann, Frank
Publié dans: Automation in Construction, 2024, ISSN 1872-7891
Éditeur: Elsevier
DOI: 10.5445/ir/1000175054

Enhancing radiomics and Deep Learning systems through the standardization of medical imaging workflows

Auteurs: Miriam Cobo; Pablo Menéndez Fernández-Miranda; Gorka Bastarrika; Lara Lloret Iglesias
Publié dans: Scientific Data, 2023, ISSN 2052-4463
Éditeur: Springer Nature
DOI: 10.1038/S41597-023-02641-X

Frouros: A Python library for drift detection in machine learning systems

Auteurs: Céspedes-Sisniega, Jaime; López-García, Álvaro
Publié dans: SoftwareX, 2022, ISSN 2352-7110
Éditeur: Elsevier
DOI: 10.1016/J.SOFTX.2024.101733

Secure Multi-Party Computation for Magnetic Resonance Imaging Classification

Auteurs: Giang Nguyen, Oleksandr Lytvyn
Publié dans: Procedia Computer Science, 2023, ISSN 1877-0509
Éditeur: Elsevier B.V.
DOI: 10.1016/j.procs.2023.03.006

Infrastructure Manager: A TOSCA-Based Orchestrator for the Computing Continuum

Auteurs: Caballer, Miguel; Moltó, Germán; Calatrava, Amanda; Blanquer, Ignacio
Publié dans: Journal of Grid Computing, 2023, ISSN 1572-9184
Éditeur: Springer Nature B.V.
DOI: 10.1007/S10723-023-09686-7

IEEE Access

Auteurs: Giang, Nguyen; Lytvyn, Oleksandr
Publié dans: IEEE Access, Numéro 12, 2024, ISSN 2169-3536
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/ACCESS.2024.3486810

Future Generation Computer Systems

Auteurs: Sebastián, Risco; Caterina, Alarcón; Sergio, Langarita; Caballer, Miguel; Moltó, Germán
Publié dans: Future Generation Computer Systems, Numéro 153, 2023, ISSN 0167-739X
Éditeur: Elsevier
DOI: 10.1016/J.FUTURE.2023.12.015

A Python library to check the level of anonymity of a dataset

Auteurs: Judith Sáinz-Pardo Díaz, Álvaro López García
Publié dans: Scientific Data, 2022, ISSN 2052-4463
Éditeur: Springer Nature
DOI: 10.1038/S41597-022-01894-2

Network security AIOps for online stream data monitoring

Auteurs: Giang Nguyen; Stefan Dlugolinsky; Viet Tran; Álvaro López García
Publié dans: Neural Computing and Applications, 2024, ISSN 1433-3058
Éditeur: Springer Nature
DOI: 10.1007/S00521-024-09863-Z

An Improved Sea Lion Optimization for Workload Elasticity Prediction with Neural Networks

Auteurs: Giang Nguyen, Binh Minh Nguyen; Trung Tran; Thieu Nguyen; Giang Nguyen
Publié dans: nternational Journal of Computational Intelligence Systems, 2022, ISSN 1875-6883
Éditeur: Springer Nature
DOI: 10.1007/s44196-022-00156-8

Study of the performance and scalability of federated learning for medical imaging with intermittent clients

Auteurs: Sáinz-Pardo Díaz, Judith; López García, Álvaro
Publié dans: Neurocomputing, Numéro 518, 2023, ISSN 1872-8286
Éditeur: Elsevier
DOI: 10.1016/J.NEUCOM.2022.11.011

A retrospective study of deep learning generalization across two centers and multiple models of X-ray devices using COVID-19 chest-X rays

Auteurs: Fernández-Miranda, P.M., Fraguela, E.M., de Linera-Alperi, M.Á. et al.
Publié dans: Nature Scientific Data, 2024, ISSN 2045-2322
Éditeur: Springer Nature
DOI: 10.1038/S41598-024-64941-5

Future Generation Computer Systems

Auteurs: Céspedes Sisniega, Jaime; Rodríguez, Vicente; Moltó, Germán; López García, Álvaro
Publié dans: Future Generation Computer Systems, Numéro 161, 2024, ISSN 0167-739X
Éditeur: Elsevier
DOI: 10.1016/j.future.2024.07.010

Personalized federated learning for improving radar based precipitation nowcasting on heterogeneous areas

Auteurs: Sinz-Pardo Daz, Judith; Castrillo, Mara; Bartok, Juraj; Heredia, Ignacio; Ondk, Irina Malkin; Martynovskyi, Ivan; Alibabaei, Khadijeh; Berberi, Lisana; Kozlov, Valentin; Lpez Garca, lvaro
Publié dans: Earth Science Informatics, 2024, ISSN 1865-0481
Éditeur: Springer Nature
DOI: 10.5445/ir/1000174167

Conference proceedings (4)

Data Partitioning Effects in Federated Learning

Auteurs: Ahmadzai, Mirwais; Nguyen, Giang
Publié dans: Software Quality Analysis, Monitoring, Improvement, and Applications 2023, 2023, ISSN 1613-0073
Éditeur: CEUR Workshop Proceedings (CEUR-WS.org)
DOI: 10.5281/zenodo.10378239

Making Federated Learning Accessible to Scientists: The AI4EOSC Approach

Auteurs: Sáinz-Pardo Díaz, Judith; Heredia Canales, Andres; Heredia, Ignacio; Viet, Tran; Nguyen, Giang; Alibabaei, Khadijeh; Obregón Ruiz, Marta; Rebolledo Ruiz, Susana; López García, Álvaro
Publié dans: IH&MMSec '24: Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security, 2024, ISBN 979-8-4007-0637-0
Éditeur: Association for Computing MachineryNew YorkNYUnited States
DOI: 10.1145/3658664.3659642

Enhancing AI development in the EOSC context: AI4EOSC and iMagine

Auteurs: Alibabaei, Khadijeh; Kozlov, Valentin; Lopez Garcia, Alvaro; Sipos, Gergely
Publié dans: IBERGRID2024, 2024
Éditeur: IBERGRID2024
DOI: 10.5281/zenodo.14056054

Comparison of machine learning models applied on anonymized data with different techniques

Auteurs: Sinz-Pardo Daz, Judith; Lpez Garca, lvaro
Publié dans: 2023 IEEE International Conference on Cyber Security and Resilience (CSR), 2023
Éditeur: IEEE