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GRAPES

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learninG pRocessing And oPtimising shapES

GRAPES aims at considerably advancing the state of the art in Mathematics, Computer-Aided Design, and Machine Learning in order to promote game changing approaches for generating, optimising, and learning 3D shapes, along with a m... ver más

31/05/2024

ATHENA - RESEARCH...

4M€

Presupuesto del proyecto: 4M€

Líder del proyecto

ATHINAEREVNITIKO KENTRO KAINOTOMIAS STIS TECH... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 12 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-05-31

MSCA-ITN-2019: Innovative Training Networks Objective:The Innovative Training Networks (ITN) aim to train a new generation of creative, entrepre...

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12 Participantes

ATHENA - RESEARCH AND INNOVA...

543.81K€ | Lider

ROTOR COMPONENTES TECNOLOGIC...

79.33K€ | Participante

501.81K€ | Participante

274.80K€ | Participante

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Duración del proyecto: 57 meses Fecha Inicio: 2019-08-09
Fecha Fin: 2024-05-31

Líder del proyecto

ATHINAEREVNITIKO KENTRO KAINOTOMIAS STIS TECH... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 4M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto GRAPES aims at considerably advancing the state of the art in Mathematics, Computer-Aided Design, and Machine Learning in order to promote game changing approaches for generating, optimising, and learning 3D shapes, along with a multisectoral training for young researchers. Recent advances in the above domains have solved numerous tasks concerning multimedia and 2D data. However, automation of 3D geometry processing and analysis lags severely behind, despite their importance in science, technology and everyday life, and the well-understood underlying mathematical principles. The CAD industry, although well established for more than 20 years, urgently requires advanced methods and tools for addressing new challenges. The scientific goal of GRAPES is to bridge this gap based on a multidisciplinary consortium composed of leaders in their respective fields. Top-notch research is also instrumental in forming the new generation of European scientists and engineers. Their disciplines span the spectrum from Computational Mathematics, Numerical Analysis, and Algorithm Design, up to Geometric Modelling, Shape Optimisation, and Deep Learning. This allows the 15 PhD candidates to follow either a theoretical or an applied track and to gain knowledge from both research and innovation through a nexus of intersectoral secondments and Network-wide workshops. Horizontally, our results lead to open-source, prototype implementations, software integrated into commercial libraries as well as open benchmark datasets. These are indispensable for dissemination and training but also to promote innovation and technology transfer. Innovation relies on the active participation of SMEs, either as a beneficiary hosting an ESR or as associate partners hosting secondments. Concrete applications include simulation and fabrication, hydrodynamics and marine design, manufacturing and 3D printing, retrieval and mining, reconstruction and visualisation, urban planning and autonomous driving.

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