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Research Topic : Ophthalmic Image Database
Australian State/Territory : QLD
Australian State/Territory : TAS
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  • Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0668073

    Funder
    Australian Research Council
    Funding Amount
    $544,000.00
    Summary
    AustLit - humanities research infrastructure development through knowledge-based dataset building, augmentation of key research elements and ICT developments. The AustLit development and augmentation program 2006-2008 will enable researchers to gain a greater understanding of the breadth and scope of Australia's conversation with the world through its literature by providing new datasets and enhanced access to the pre-eminent resource to our literary culture. AustLit aims to deliver authoritativ .... AustLit - humanities research infrastructure development through knowledge-based dataset building, augmentation of key research elements and ICT developments. The AustLit development and augmentation program 2006-2008 will enable researchers to gain a greater understanding of the breadth and scope of Australia's conversation with the world through its literature by providing new datasets and enhanced access to the pre-eminent resource to our literary culture. AustLit aims to deliver authoritative information and analysable data about all Australian writers and their writing and in 2006 will develop specialist datasets relating to Aboriginal and Torres Strait Islander writers; multicultural writers; and regional and colonial writing from Tasmania and Qld. ICT developments will provide other collaborative groups with an opportunity to use a highly successful middleware platform for new KM projects.
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    Funded Activity

    Super Science Fellowships - Grant ID: FS100100043

    Funder
    Australian Research Council
    Funding Amount
    $278,400.00
    Summary
    Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching f .... Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching for ecological patterns on a national scale that would be difficult to identify using traditional approaches tuned to process-scale studies. Australian society stands to benefit by virtue of improved large-scale models of ecosystem function and reduced cost for conducting marine ecosystem investigations.
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    Active Funded Activity

    Industrial Transformation Research Hubs - Grant ID: IH180100002

    Funder
    Australian Research Council
    Funding Amount
    $5,000,000.00
    Summary
    ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. Thes .... ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. These dynamic systems will help determine what goal to achieve and the most efficient plan to achieve it. This Hub is expected to contribute to higher farming efficiency, lower production costs and fewer disease risks, giving the Australian industry new business opportunities and an international competitive advantage.
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