Objective
Europe's media sector is strong in creating content but lacks behind in embracing new technologies and new business models. Competition from global players that are strong at technological innovation is increasing fast. This puts many jobs, original European content and cultural heritage at risk.
The future of broadcasters is in metadata management. This data is used to fuel media applications. These will be the backbone of future television and will be used to schedule programming, interactive programming, video discovery and targeted advertising. But still today, broadcasters rely on manual labelling by editors to tag the key content of their media. The holy grail here is to do this automatically, more extensively and in real-time.
We are Media Distillery and we developed a platform that analyses every millisecond of audio and video content in real-time. We produce the most extensive deep media metadata seen in the industry. By using cutting edge deep learning, artificial intelligence and state of the art data mining techniques, our platform filters all relevant information. The current Media Distillery Platform is already well proven in providing Media Metadata services, and we already serve ten international clients.
The aim of this project is to enhance and commercialize our Metadata Distillery and ExpLoitation System (MoDELS). This enables the widespread uptake of our Deep content understanding technology and associated applications. In this project we will demonstrate its effectiveness in four media applications at European TV operators. Demonstrating that with our advanced metadata, content catalogues are better managed, content descriptions are more accurate, searching is far more exhaustively and recommendations more useful. Hereby realising business opportunities for TV operators that were unimaginable before. They understand customers better, improve their business processes, increase revenue, reduce costs and improve decision making.
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 artificial intelligence computer vision facial recognition
- social sciences economics and business economics
- natural sciences computer and information sciences data science data mining
- social sciences economics and business business and management business models
- natural sciences computer and information sciences artificial intelligence machine learning deep 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.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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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.
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.
SME-2 - SME instrument phase 2
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1066 EP AMSTERDAM
Netherlands
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.