DEEPCEPTION
Financiado
Visual perception in deep neural networks
How do we recognize what we see? Despite the deceptive ease of perceiving things, explaining how we see turns out to be a supremely difficult task. Only recently advances in computer vision finally brought a class of models, known...
How do we recognize what we see? Despite the deceptive ease of perceiving things, explaining how we see turns out to be a supremely difficult task. Only recently advances in computer vision finally brought a class of models, known as deep neural nets, that are capable of matching human performance in several visual perception tasks. In this project, we aim to employ the knowledge how human visual system processes visual information in order to critically evaluate and improve the existing models of vision. Our aim is twofold. On the one hand, little is known yet how well deep nets can account for a huge variety of tasks that human visual system faces daily. We will perform a broad battery of tests in order to shed light on the power of deep nets and to spot potential limitations. Capitalizing on these shortcomings, in the second part of this project we aim to improve the existing technology by introducing novel algorithms based on behavioral and neural data of humans. Taken together, this project will lay a solid foundation for the psychologically- and biologically-based development of the next generation of deep nets.
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Duración del proyecto: 43 meses
Fecha Inicio: 2016-02-29
Fecha Fin: 2019-09-30
Fecha Fin: 2019-09-30
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2019-09-30
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
MSCA-IF-2015-GF:
Marie Skłodowska-Curie Individual Fellowships (IF-GF)
Cerrada
hace 9 años
Presupuesto
El presupuesto total del proyecto asciende a
259K€
Líder del proyecto
KATHOLIEKE UNIVERSITEIT LEUVEN
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
258.13K€ |
Participante