Objective
The objective is to build a Europe-wide Distributed Institute which will pioneer principled methods of pattern analysis, statistical modelling, and computational learning as core enabling technologies for multi-modal interfaces that are capable of natural and seamless interaction with and among individual human users.
At each stage in the process, machine learning has a crucial role to play. It is proving an increasingly important tool in Machine Vision, Speech, Haptics, Brain Computer Interfaces Information Extraction and Natural Language Processing; it provides a uniform methodology for multi-modal integration; it is an invaluable tool in information extraction; while on-line learning provides the techniques needed for adaptively modelling the requirements of individual users.
Though machine learning has such potential to improve the quality of multi-modal interfaces, significant advances are needed, in both the fundamental techniques and their tailoring to the various aspects of the applications, before this vision can become a reality. We therefore propose to establish an inter-disciplinary Europe-wide Distributed Institute of Pattern Analysis, Statistical Modelling, and Computational Learning. The Institute will foster interaction between groups working on fundamental analysis including statisticians and learning theorists; algorithms groups including members of the non-linear programming community; and groups in machine vision, speech, haptics, brain-computer interfaces, natural language processing, information-retrieval, textual information processing and user modelling for computer-human interaction, groups that will act as bridges to the application domains and end users.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdata sciencenatural language processing
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesdata sciencedata processing
Call for proposal
Data not availableFunding Scheme
NoE - Network of ExcellenceCoordinator
SO17 1BJ SOUTHAMPTON
United Kingdom
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Participants (56)
9220 AALBORG
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B4 7ET BIRMINGHAM
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52900 RAMAT GAN
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75794 PARIS CEDEX 16
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2800 KGS. LYNGBY
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8092 ZUERICH
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80686 MUENCHEN
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02015 ESPOO
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1920 MARTIGNY
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SW7 2AZ LONDON
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77305 FONTAINEBLEAU CEDEX
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78153 LE CHESNAY
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76130 MONT ST AIGNAN
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1000 LJUBLJANA
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1001 LJUBLJANA
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3000 LEUVEN
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WC2R 2LS LONDON
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100 44 STOCKHOLM
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80539 MUENCHEN
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8700 LEOBEN
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CANBERRA
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TW20 0EX EGHAM, SURREY
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44780 BOCHUM
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1098 SJ AMSTERDAM
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5612AZ EINDHOVEN
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6525 EZ NIJMEGEN
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5230 ODENSE M
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32000 HAIFA
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8010 GRAZ
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69978 TEL AVIV
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OXFORD
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91904 JERUSALEM
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WC2A 2AE LONDON
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EH8 9YL EDINBURGH
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G12 8QQ GLASGOW
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S10 2TN SHEFFIELD
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CV4 7AL COVENTRY
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03690 SAN VICENTE DEL RASPEIG (ALICANTE)
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16126 GENOVA
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20122 MILANO
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21100 VARESE
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4003 BASEL
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95447 BAYREUTH
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08034 BARCELONA
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08002 BARCELONA
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84029 AVIGNON
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1211 GENEVE 4
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42023 SAINT-ETIENNE
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75252 PARIS CEDEX 05
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91405 ORSAY
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2000 ANTWERPEN
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2311 EZ LEIDEN
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WC1E 6BT LONDON
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BS8 1TH BRISTOL
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02570 SIUNTIO KK
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93607 AULNAY-SOUS-BOIS
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