Obiettivo "Future data processing challenges in science will enter the ""Big Data"" era, involving massive, as well as complex and heterogeneous data. Extracting, with high precision, every bit of information from scientific data requires overcoming fundamental statistical challenges, which mandate the design of dedicated methods that must be both effective enough to capture the intricacy of real-world datasets and robust to the high complexity of instrumental measurements. Moreover, future datasets, such as those provided by the space mission Euclid, will involve at least gigascale data, which will make mandatory the development of new, physically relevant, data models and the implementation of effective and computationally efficient processing tools. The recent emergence of novel data analysis methods in machine learning should foster a new modeling framework, allowing for a better preservation of the intrinsic physical properties of real data that generally live on intricate spaces, such as signal manifolds. Furthermore, advances in operations research and optimization theory pave the way for effective solutions to overcome the large-scale data processing bottlenecks. In this context, the objective of the DEDALE project is threefold: i) introduce new models and methods to analyze and restore complex, multivariate, manifold-based signals; ii) exploit the current knowledge in optimization and operations research to build efficient numerical data processing algorithms in the large-scale settings; and iii) show the reliability of the proposed data modeling and analysis technologies to tackle Scientific Big Data challenges in two different applications: one in cosmology, to map the dark matter mass map of the universe, and one in remote sensing to increase the capabilities of automatic airborne imaging analysis systems." Campo scientifico natural sciencescomputer and information sciencesdata sciencebig datanatural sciencesphysical sciencesastronomyastrophysicsdark matternatural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learningnatural sciencesphysical sciencesastronomyphysical cosmologynatural sciencescomputer and information sciencesdata sciencedata processing Parole chiave wavelets dictionary learning manifold weak lensing remote sensing Programma(i) H2020-EU.1.2. - EXCELLENT SCIENCE - Future and Emerging Technologies (FET) Main Programme H2020-EU.1.2.1. - FET Open Argomento(i) FETOPEN-RIA-2014-2015 - FET-Open research projects Invito a presentare proposte H2020-FETOPEN-2014-2015 Vedi altri progetti per questo bando Bando secondario H2020-FETOPEN-2014-2015-RIA Meccanismo di finanziamento RIA - Research and Innovation action Coordinatore COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES Contribution nette de l'UE € 857 875,00 Indirizzo RUE LEBLANC 25 75015 PARIS 15 Francia Mostra sulla mappa Regione Ile-de-France Ile-de-France Paris Tipo di attività Research Organisations Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 857 875,00 Partecipanti (4) Classifica in ordine alfabetico Classifica per Contributo netto dell'UE Espandi tutto Riduci tutto IDRYMA TECHNOLOGIAS KAI EREVNAS Grecia Contribution nette de l'UE € 560 000,00 Indirizzo N PLASTIRA STR 100 70013 Irakleio Mostra sulla mappa Regione Νησιά Αιγαίου Κρήτη Ηράκλειο Tipo di attività Research Organisations Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 560 000,00 SAFRAN ELECTRONICS & DEFENSE Francia Contribution nette de l'UE € 288 125,00 Indirizzo 2 BOULEVARD DU GENERAL MARTIAL VALIN 75015 Paris Mostra sulla mappa Regione Ile-de-France Ile-de-France Paris Tipo di attività Private for-profit entities (excluding Higher or Secondary Education Establishments) Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 288 125,00 UNIVERSITY COLLEGE LONDON Regno Unito Contribution nette de l'UE € 485 397,50 Indirizzo GOWER STREET WC1E 6BT London Mostra sulla mappa Regione London Inner London — West Camden and City of London Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 485 397,50 TECHNISCHE UNIVERSITAT BERLIN Germania Contribution nette de l'UE € 511 000,00 Indirizzo STRASSE DES 17 JUNI 135 10623 Berlin Mostra sulla mappa Regione Berlin Berlin Berlin Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 511 000,00
