Objective
Due to the convergence of several strands of scientific and technological progress we are witnessing the emergence of unprecedented opportunities for the creation of a knowledge driven society. Indeed, databases are accruing large amounts of complex multimedia documents, networks allow fast and almost ubiquitous access to an abundance of resources and processors have the computational power to perform sophisticated and demanding algorithms.
However, progress is hampered by the sheer amount and diversity of the available data. As a consequence, access can only be efficient if based directly on content and semantics, the extraction and indexing of which is only feasible if achieved automatically. MUSCLE aims at creating and supporting a pan-European Network of Excellence to foster close collaboration between research groups in multimedia data mining on the one hand and machine learning on the other in order to make breakthrough progress towards the following objectives.(i) Harnessing the full potential of machine learning and cross-modal interaction for the (semi-)automatic generation of metadata with high semantic content for multimedia documents.(ii) Applying machine learning for the creation of expressive, context-aware, self-learning, and human centred interfaces that will be able to effectively assist users in the exploration of complex and rich multimedia content.(iii) Improving interoperability and exchangeability of heterogeneous and distributed (meta)data try enabling data descriptions of high semantic content (e.g. ontologies, MPEG7 and XML schemata) an conference schemes that can reason about these at the appropriate levels.(iv) Through dissemination, training and industrial liaison, contribute to the distribution and uptake the technology by relevant end-users such as industry, education, and the service sector.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences databases
- natural sciences computer and information sciences data science data mining
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
06410 BIOT
France
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Participants (37)
182 08 PRAHA
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1220 WIEN
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79085 FREIBURG
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1220 WIEN
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54124 THESSALONIKI
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75272 PARIS
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06533 ANKARA
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75794 PARIS CEDEX 16
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75752 PARIS CEDEX 15
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00185 ROMA
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95014 CERGY CEDEX
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1220 WIEN
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71110 IRAKLIO, CRETE
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75013 PARIS 13
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04107 LEIPZIG
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78153 LE CHESNAY
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10682 ATHENS
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100 44 STOCKHOLM
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75008 PARIS 08
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1111 BUDAPEST
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1098 SJ AMSTERDAM
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32000 HAIFA
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8010 GRAZ
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1040 WIEN
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69978 TEL AVIV
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73100 CHANIA
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CB2 1TS CAMBRIDGE
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2 DUBLIN
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GU2 7XH GUILDFORD
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08034 BARCELONA
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75252 PARIS CEDEX 05
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1012 WX AMSTERDAM
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DUBLIN 4
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WC1E 6BT LONDON
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BT52 1SA COLERAINE
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02044 VTT
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