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Status : Active
Socio-Economic Objective : Expanding Knowledge in Engineering
Research Topic : Low Vision
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  • Researchers (54)
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP210104074

    Funder
    Australian Research Council
    Funding Amount
    $192,500.00
    Summary
    In-vivo functional imaging of cone photoreceptors and ganglion cell axons. Can we project a movie on a human retina, and measure the response of photoreceptor cells and connected nerve tissue? This project aims to investigate a new method for visualization of the quickest responses in human cone photoreceptors and nerve cells after a visible stimulus. Expected outcomes of this project include a better understanding of the origins of responses to a stimulus and how cells in the retina communicate .... In-vivo functional imaging of cone photoreceptors and ganglion cell axons. Can we project a movie on a human retina, and measure the response of photoreceptor cells and connected nerve tissue? This project aims to investigate a new method for visualization of the quickest responses in human cone photoreceptors and nerve cells after a visible stimulus. Expected outcomes of this project include a better understanding of the origins of responses to a stimulus and how cells in the retina communicate. The scientific results will be helpful in a better understanding of the development of vision in the infant eye, to study peripheral vision in elite athletes and to quantify performance of virtual reality equipment for the military. The IP on the technology can be licensed or used for start-up company.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP180102287

    Funder
    Australian Research Council
    Funding Amount
    $618,912.00
    Summary
    Ultra-low fouling active surfaces. This project aims to develop chemistries and fabrication approaches through innovative materials evaluation to develop ultra-low fouling active electrode surfaces. Development of ultra-low fouling surfaces will have significant impact in a range of applications where system or device failure is attributed to fouling. The growing field of bionics, where implantable electronic devices interface directly with the nervous system, is one such device. The expected ou .... Ultra-low fouling active surfaces. This project aims to develop chemistries and fabrication approaches through innovative materials evaluation to develop ultra-low fouling active electrode surfaces. Development of ultra-low fouling surfaces will have significant impact in a range of applications where system or device failure is attributed to fouling. The growing field of bionics, where implantable electronic devices interface directly with the nervous system, is one such device. The expected outcomes will be an understanding of the material requirements that lead to the elimination of protein and cell accumulation at surfaces that degrades the performance and lifetime of these implants. The findings will benefit any application where fouling is a problem.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT190100525

    Funder
    Australian Research Council
    Funding Amount
    $988,200.00
    Summary
    Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collabor .... Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collaborations with machine learning and medical image analysis research institutions. This should provide significant benefits, such as better understanding of deep learning theory, new deep learning applications that can use previously unexplored data sets, and training for the future Australian workforce.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT170100072

    Funder
    Australian Research Council
    Funding Amount
    $808,140.00
    Summary
    The role of strong duality in computer vision. This project aims to undertake research in the fields of computer vision and optimization that will have a significant impact on the design of numerical algorithms for solving a wide range of problems in Computer Vision, Virtual Reality and Robotic Navigation. This project will advance understanding of a broad class of problems related to how computers interpret images. An expected outcome is the generation of novel mathematical theory and numerical .... The role of strong duality in computer vision. This project aims to undertake research in the fields of computer vision and optimization that will have a significant impact on the design of numerical algorithms for solving a wide range of problems in Computer Vision, Virtual Reality and Robotic Navigation. This project will advance understanding of a broad class of problems related to how computers interpret images. An expected outcome is the generation of novel mathematical theory and numerical algorithms capable of fundamentally changing the way problems relevant to a wide range of vision-related applications are solved. This should offer Australia a strong competitive advantage as a leader in scientific innovation in the areas of Computer Vision, Virtual Reality and Robotics and Autonomous Systems.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220102933

    Funder
    Australian Research Council
    Funding Amount
    $417,516.00
    Summary
    Developmental trajectory of tongue control for speech with real-time MRI. This project aims to evaluate the developmental trajectory of tongue control during speech, relating dynamic 3D vocal tract modelling to the acoustic signal. By optimising real-time MRI technology to capture and model articulatory movements, the project expects to accelerate understanding of how tongue control for speech is developed, mastered, and perturbed by factors such as rapid growth and foreign accent. Expected outc .... Developmental trajectory of tongue control for speech with real-time MRI. This project aims to evaluate the developmental trajectory of tongue control during speech, relating dynamic 3D vocal tract modelling to the acoustic signal. By optimising real-time MRI technology to capture and model articulatory movements, the project expects to accelerate understanding of how tongue control for speech is developed, mastered, and perturbed by factors such as rapid growth and foreign accent. Expected outcome is a new understanding of how different speakers' vocal tracts change and how speech is reshaped, informed by real physiological data. Significant benefits will be realised through refined methods and theory development for diverse fields e.g. linguistics, speech science, and automatic speech recognition/synthesis.
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