Objective
The latest achievements in artificial intelligence and neural networks, especially deep neural architecture in large-scale neuromorphic hardware implementation such as SpiNNaker, and in cognitive robotics and neurorobotics, with the widespread use of robots such as iCub and the latest Pepper platform, provide the opportunity to significantly advance our understand human cognition and brains and to reach human-level artificial intelligence. One of the key success factors in deep learning is its hierarchical structure inspired by biological processes in the primate visual cortex, as with convolutional deep networks able to learn rich representations. They are grounded in optimization methods with high precision for training may consume large training datasets and computational resources to learn complex tasks. That gives human level performance in static image recognition but raises adaptation issues. SpiNNaker is a neuromorphic computer architecture in massively parallel computing platform based on spiking neural networks (SNNs) in which neurons communicate by temporal code. The aim of STRoNA (Spatio-Temporal Representation on Neuromorphic Architecture) is to define the technology that will map a computational architecture onto neuromorphic computing circuits, hence to develop a cognitive model with spatio-temporal representation and learning algorithm for humanoid robots.
The principal research objectives of the project are: (i) to investigate which spatio-temporal representations of spikes (or neural action potentials) can be used to achieve human level performance on visual perception; (ii) to develop a novel method to process spatio-temporal representation on a neuromorphic architecture to enable learning in online and interactive contexts; and (iii) to validate and adapt the developed system in real world robotics applications.
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.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics cognitive robots
- natural sciences computer and information sciences artificial intelligence computer vision image recognition
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics autonomous robots
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- natural sciences computer and information sciences artificial intelligence computational intelligence
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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.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
MSCA-IF-EF-ST - Standard EF
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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-MSCA-IF-2017
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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.
M13 9PL Manchester
United Kingdom
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.