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Australian State/Territory : QLD
Research Topic : computer
Socio-Economic Objective : Expanding Knowledge in Engineering
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP200100336

    Funder
    Australian Research Council
    Funding Amount
    $274,933.00
    Summary
    Design guidelines for safety-critical controllers in high-risk environments. This project aims to generate novel product design guidelines for developing safer controllers for use by potentially stressed individuals in high-risk situations. It will do this by generating specific insights and verifying generalisable solutions from the context of total artificial heart recipients –who must engage with critical controllers constantly. This project expects to generate new knowledge in design by esta .... Design guidelines for safety-critical controllers in high-risk environments. This project aims to generate novel product design guidelines for developing safer controllers for use by potentially stressed individuals in high-risk situations. It will do this by generating specific insights and verifying generalisable solutions from the context of total artificial heart recipients –who must engage with critical controllers constantly. This project expects to generate new knowledge in design by establishing a new research topic around an under-examined user cohort. Expected outcomes of this project include interaction design theory developments and improved controller design techniques. This should provide significant benefits and competitive advantages by lowering stress and improving safety across a range of contexts.
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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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    Funded Activity

    Discovery Projects - Grant ID: DP140102794

    Funder
    Australian Research Council
    Funding Amount
    $295,000.00
    Summary
    Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t .... Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.
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    Funded Activity

    Discovery Projects - Grant ID: DP140103216

    Funder
    Australian Research Council
    Funding Amount
    $336,000.00
    Summary
    Human Cues for Robot Navigation. The world has many navigational cues for the benefit of humans: sign posts, maps and the wealth of information on the internet. Yet, to date, robotic navigation has made little use of this abundant symbolic information as a resource. This project will develop a robot navigation system that can navigate using information beyond the robot's range sensors by incorporating knowledge gained by reading room labels, following human route directions or interpreting maps .... Human Cues for Robot Navigation. The world has many navigational cues for the benefit of humans: sign posts, maps and the wealth of information on the internet. Yet, to date, robotic navigation has made little use of this abundant symbolic information as a resource. This project will develop a robot navigation system that can navigate using information beyond the robot's range sensors by incorporating knowledge gained by reading room labels, following human route directions or interpreting maps found on the web. This project will demonstrate the robot's navigation ability by comparing its performance with a human as it learns to find its way around campus by asking for directions, reading signs and maps, and searching the internet for clues.
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    Funded Activity

    Discovery Projects - Grant ID: DP180103232

    Funder
    Australian Research Council
    Funding Amount
    $387,884.00
    Summary
    Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the .... Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.
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