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Research Topic : Image processing
Field of Research : Sensory Systems
Australian State/Territory : SA
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Artificial Intelligence and Image Processing not elsewhere classified (4)
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  • Funded Activity

    Discovery Projects - Grant ID: DP130104572

    Funder
    Australian Research Council
    Funding Amount
    $370,000.00
    Summary
    Neural mechanisms for visual target detection and attention in complex scenes. This project will study neurons in the insect brain that solve one of the biggest problems for computer vision systems - tracking the motion of tiny targets moving against strongly camouflaged backgrounds. The results will be used to develop a novel biologically inspired model for target tracking with applications for smart cameras and robotics.
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    Funded Activity

    Discovery Projects - Grant ID: DP130104561

    Funder
    Australian Research Council
    Funding Amount
    $430,000.00
    Summary
    Strategies for neural summation in space and time for night vision. This project will study motion vision in nocturnal and day-active insects to understand how the brain sees in darkness, even when individual light sensitive cells in the eye perform poorly. This will help to identify optimal strategies that have evolved in nature to deal with noisy signals in low light and has implications for man-made night cameras.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT180100466

    Funder
    Australian Research Council
    Funding Amount
    $857,189.00
    Summary
    From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden .... From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden behind another object. This project will investigate how brains use both environmental and internal information to select a target and predict its future location. By implementing bio-inspired computations in hardware, this project aims to provide significant benefits such as improving autonomous systems for defence, health and transportation.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE150100548

    Funder
    Australian Research Council
    Funding Amount
    $359,000.00
    Summary
    Neural and robotic correlates of predictive coding and selective attention. Whether a human catching a ball, a dog leaping at a frisbee or a dragonfly hunting prey amidst a swarm, brains both large and small have evolved the ability to focus attention on one moving target, even in the presence of distracters. This project aims to investigate how brains solve this challenging problem by recording the activity of dragonfly neurons that selectively attend to one target whilst ignoring others. The p .... Neural and robotic correlates of predictive coding and selective attention. Whether a human catching a ball, a dog leaping at a frisbee or a dragonfly hunting prey amidst a swarm, brains both large and small have evolved the ability to focus attention on one moving target, even in the presence of distracters. This project aims to investigate how brains solve this challenging problem by recording the activity of dragonfly neurons that selectively attend to one target whilst ignoring others. The project aims to examine how expectation and attention are encoded in the brain and will build an autonomous robot using computational models bio-inspired from this neuronal processing. Robots capable of visually perceiving and interacting with targets in natural environments have applications in health, surveillance and defence.
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