SOURCE-LINKED INTELLIGENCE

It's about time: Towards a dynamic account of natural vision.

CORDIS · observation · Publication date unknown

visually explore tens of thousands of rich human-annotated natural scenes, the development of novel multivariate analysis techniques, and large-scale computational modelling using a new bio-inspired deep learning framework for active vision that closes the sensory-motor loop. Using this interdisciplinary approach, TIME will establish, for the first time, when, where, and how visual semantic understanding emerges in the brain as it actively samples and integrates information from the world in a continuously updating and dynamic decision process. These ground-breaking developments both in experimentation and deep neural network modelling build towards a fundamental paradigm shift in how we study, model, and understand vision, yielding new insights into its complex neural processes operating in more natural, ecologically valid conditions, as well as a closer alignment between biological and synthetic vision. human vision, visual system, eye-movements, recurrence, dynamics, semantics, computational modelling, deep learning, deep reinforcement learning, machine learning, neuroscience

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recordType

award

status

SIGNED

region

EU

value

1499455

unit

EUR