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Australian State/Territory : QLD
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Research Topic : Signal processing
Field of Research : Computer Vision
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  • Funded Activity

    Discovery Projects - Grant ID: DP0344338

    Funder
    Australian Research Council
    Funding Amount
    $242,242.00
    Summary
    An automated 3D model-based object recognition system. A novel, practical 3D vision system is proposed as a platform for fundamental applied research in 3D data acquisition, object modelling and object recognition. The significance of the vision system lies in the advancement of knowledge in three key areas of computer vision, registration, recognition and error propagation. The result is a system capable of sensing, modelling and identifying arbitrarily shaped free-form objects in a scene, an a .... An automated 3D model-based object recognition system. A novel, practical 3D vision system is proposed as a platform for fundamental applied research in 3D data acquisition, object modelling and object recognition. The significance of the vision system lies in the advancement of knowledge in three key areas of computer vision, registration, recognition and error propagation. The result is a system capable of sensing, modelling and identifying arbitrarily shaped free-form objects in a scene, an attribute lacking in current systems. Such a system can provide substantial economic benefits to industrial procedures such as grasp planning and quality control.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100221

    Funder
    Australian Research Council
    Funding Amount
    $420,000.00
    Summary
    Monitoring intuitive expertise in the context of airport security screening. During airport security screening and processing, confusion and error are greatest when systems or contexts are unfamiliar. Poorly designed systems compromise the interactions of airport security personnel and decrease their ability to promptly and accurately respond to situations. This project aims to deliver a suite of automated methods to monitor security operator knowledge and engagement, to assess the real-time sec .... Monitoring intuitive expertise in the context of airport security screening. During airport security screening and processing, confusion and error are greatest when systems or contexts are unfamiliar. Poorly designed systems compromise the interactions of airport security personnel and decrease their ability to promptly and accurately respond to situations. This project aims to deliver a suite of automated methods to monitor security operator knowledge and engagement, to assess the real-time security screening context, and to detect unusual passenger behaviour at the screening check-point. This monitoring aims to provide new knowledge and techniques to enhance security operator performance, refine the screening process, improve passenger experience and, most critically, ensure safety at Australian airports.
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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

    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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    Showing 1-4 of 4 Funded Activites

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