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Research Topic : Mathematical Software
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  • Funded Activity

    Research Networks - Grant ID: RN0460006

    Funder
    Australian Research Council
    Funding Amount
    $1,500,000.00
    Summary
    ARC Complex Open Systems Research Network. Complexity is the common frontier in the physical, biological and social sciences. This Network will link specialists in all three sciences through five generic conceptual and mathematical theme activities. It will promote research into how subsystems self-organise into new emergent structures when assembled into an open, non-equilibrium system. Outcomes will include new technologies and software tools and deeper understanding of fundamental questions i .... ARC Complex Open Systems Research Network. Complexity is the common frontier in the physical, biological and social sciences. This Network will link specialists in all three sciences through five generic conceptual and mathematical theme activities. It will promote research into how subsystems self-organise into new emergent structures when assembled into an open, non-equilibrium system. Outcomes will include new technologies and software tools and deeper understanding of fundamental questions in science. An essential function of the network will be introducing researchers end users to new tools and broadening the horizons of graduate students.
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    Funded Activity

    Linkage Projects - Grant ID: LP160100495

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including comm .... Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including communications and navigational satellites, in Earth’s orbit from collisions and covert sabotage. Increased space use by government and civilian agencies opens up opportunities for the space industry. This project is expected to develop Australia’s space surveillance capabilities, protect space assets and capture a growing market.
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    Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models: The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object .... Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models: The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180100284

    Funder
    Australian Research Council
    Funding Amount
    $461,783.00
    Summary
    Photogrammetric Reconstruction for Underwater Virtual Heritage Experiences. This project aims to enable significant underwater cultural heritage sites such as shipwrecks to be recreated in immersive underwater virtual heritage experiences. Photogrammetric 3D reconstruction techniques will be used to generate complex digital 3D models of shipwreck sites from hundreds of thousands of underwater images. This will allow vivid experiences to be created which explain the stories of these wrecks. The p .... Photogrammetric Reconstruction for Underwater Virtual Heritage Experiences. This project aims to enable significant underwater cultural heritage sites such as shipwrecks to be recreated in immersive underwater virtual heritage experiences. Photogrammetric 3D reconstruction techniques will be used to generate complex digital 3D models of shipwreck sites from hundreds of thousands of underwater images. This will allow vivid experiences to be created which explain the stories of these wrecks. The project will conduct audience engagement studies to recommend the most appropriate methods to implement underwater virtual heritage experiences for Australian audiences. The sites which will be used as test datasets are some of the most significant Australian shipwreck sites, including HMAS Sydney (II) and HMAS AE1.
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    Funded Activity

    Research Networks - Grant ID: RN0459557

    Funder
    Australian Research Council
    Funding Amount
    $1,950,000.00
    Summary
    ARC Research Network for a Secure Australia. The Research Network for a Secure Australia (RNSA) is a multi-disciplinary collaboration established to strengthen Australia's research capacity for protecting critical infrastructure from natural or human-caused disasters including terrorist acts. The RNSA will facilitate a knowledge-sharing network for research organisations, government and the private sector to develop research tools and methods to mitigate emerging safety and security issues relat .... ARC Research Network for a Secure Australia. The Research Network for a Secure Australia (RNSA) is a multi-disciplinary collaboration established to strengthen Australia's research capacity for protecting critical infrastructure from natural or human-caused disasters including terrorist acts. The RNSA will facilitate a knowledge-sharing network for research organisations, government and the private sector to develop research tools and methods to mitigate emerging safety and security issues relating to critical infrastructure. World-leaders with extensive national and international linkages in relevant scientific, engineering and technological research will lead this collaboration. The RNSA will launch various activities to foster research collaboration and nurture young investigators.
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