The following table provides information about the project.
WESTFAELISCHE WILHELMS-UNIVERSITAET MUENSTER
|Coordinator Country||Germany [DE]|
|Total cost||1˙111˙500 €|
|EC max contribution||1˙111˙500 € (100%)|
1. H2020-EU.1.3.3. (Stimulating innovation by means of cross-fertilisation of knowledge)
|Duration (year-month-day)||from 2018-03-01 to 2022-02-28|
Take a look of project's partnership.
|1||WESTFAELISCHE WILHELMS-UNIVERSITAET MUENSTER||DE (MUENSTER)||coordinator||229˙500.00|
|2||THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE||UK (CAMBRIDGE)||participant||238˙500.00|
|3||UNIVERSITEIT TWENTE||NL (ENSCHEDE)||participant||112˙500.00|
|4||THE UNIVERSITY OF NOTTINGHAM||UK (NOTTINGHAM)||participant||81˙000.00|
|5||UNIVERSITE DE BORDEAUX||FR (BORDEAUX)||participant||76˙500.00|
|6||ECOLE NATIONALE SUPERIEURE D'INGENIEURS DE CAEN||FR (CAEN)||participant||54˙000.00|
|7||INSTITUTO SUPERIOR TECNICO||PT (LISBOA)||participant||54˙000.00|
|8||Ecole Polytechnique of Paris||FR (PALAISEAU CEDEX)||participant||40˙500.00|
|9||UNIVERSITA DEGLI STUDI DI GENOVA||IT (GENOVA)||participant||40˙500.00|
|10||TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY||IL (HAIFA)||participant||36˙000.00|
|11||UNIVERSITE DE CAEN NORMANDIE||FR (CAEN CEDEX 5)||participant||36˙000.00|
|12||UNIVERSITE LYON 1 CLAUDE BERNARD||FR (VILLEURBANNE CEDEX)||participant||31˙500.00|
|13||CAMELOT BIOMEDICAL SYSTEMS SRL||IT (GENOVA)||participant||27˙000.00|
|14||MEDIGUIDE LTD||IL (HAIFA)||participant||27˙000.00|
|15||UNIVERSIDAD POMPEU FABRA||ES (BARCELONA)||participant||22˙500.00|
|16||POLITECNICO DI MILANO||IT (MILANO)||participant||4˙500.00|
|17||ASTRAZENECA UK LIMITED||UK (CAMBRIDGE)||participant||0.00|
|18||CLINICAL SCIENCE SYSTEMS||NL (LEIDEN)||participant||0.00|
|19||CLK GMBH||DE (ALTENBERGE)||participant||0.00|
|21||THE MATHWORKS LIMITED||UK (CAMBRIDGE CAMBS)||participant||0.00|
|22||CARNEGIE MELLON UNIVERSITY||US (PITTSBURGH)||partner||0.00|
|23||THE REGENTS OF THE UNIVERSITY OF CALIFORNIA||US (OAKLAND CA)||partner||0.00|
In NoMADS we focus on data processing and analysis techniques which can feature potentially very complex, nonlocal, relationships within the data. In this context, methodologies such as spectral clustering, graph partitioning, and convolutional neural networks have gained increasing attention in computer science and engineering within the last years, mainly from a combinatorial point of view. However, the use of nonlocal methods is often still restricted to academic pet projects. There is a large gap between the academic theories for nonlocal methods and their practical application to real-world problems. The reason these methods work so well in practice is far from fully understood. Our aim is to bring together a strong international group of researchers from mathematics (applied and computational analysis, statistics, and optimisation), computer vision, biomedical imaging, and remote sensing, to fill the current gaps between theory and applications of nonlocal methods. We will study discrete and continuous limits of nonlocal models by means of mathematical analysis and optimisation techniques, resulting in investigations on scale-independent properties of such methods, such as imposed smoothness of these models and their stability to noisy input data, as well as the development of resolution-independent, efficient and reliable computational techniques which scale well with the size of the input data. As an overarching applied theme we focus in particular on image data arising in biology and medicine, which offers a rich playground for structured data processing and has direct impact on society, as well as discrete point clouds, which represent an ambitious target for unstructured data processing. Our long-term vision is to discover fundamental mathematical principles for the characterisation of nonlocal operators, the development of new robust and efficient algorithms, and the implementation of those in high quality software products for real-world application.
Work performed, outcomes and results: advancements report(s)
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The information about "NOMADS" are provided by the European Opendata Portal: CORDIS opendata.
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