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From single neurons to visual perception

Objectif

We propose to develop a formal model of information representation and processing in the part of the neocortex that is mostly concerned with visual information. This model will open new horizons in a well-principled way in the fields of artificial and biological vision as well as in computational neuroscience. Specifically the goal is to develop a universally accepted formal framework for describing complex, distributed and hierarchical processes capable of processing seamlessly a continuous flow of images. This framework features notably computational units operating at several spatiotemporal scales on stochastic data arising from natural images. Mean-field theory and stochastic calculus are used to harness the fundamental stochastic nature of the data, functional analysis and bifurcation theory to map the complexity of the behaviours of these assemblies of units. In the absence of such foundations the development of an understanding of visual information processing in man and machines could be greatly hindered. Although the proposal addresses fundamental problems its goal is to serve as the basis for ground-breaking future computational development for managing visual data and as a theoretical framework for a scientific understanding of biological vision.

Appel à propositions

ERC-2008-AdG
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Régime de financement

ERC-AG - ERC Advanced Grant

Institution d’accueil

INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE
Contribution de l’UE
€ 1 706 839,00
Adresse
DOMAINE DE VOLUCEAU ROCQUENCOURT
78153 Le Chesnay Cedex
France

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Région
Ile-de-France Ile-de-France Yvelines
Type d’activité
Research Organisations
Contact administratif
Frédérique Lavirotte (Ms.)
Chercheur principal
Olivier Dominique Faugeras (Dr.)
Liens
Coût total
Aucune donnée

Bénéficiaires (1)