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Australian State/Territory : ACT
Field of Research : Knowledge Representation And Machine Learning
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Knowledge Representation And Machine Learning (6)
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  • Funded Activity

    Discovery Projects - Grant ID: DP0773761

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, .... Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT0990811

    Funder
    Australian Research Council
    Funding Amount
    $686,400.00
    Summary
    Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications .... Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications including consistency checking and spatial query pre-processing. The project will help in extracting knowledge from massive spatial databases, meeting the growing needs of naive users for spatial information and establishing Australia as a major player in spatial cognition research and in the development of geo-location services.
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    Funded Activity

    Discovery Projects - Grant ID: DP0452731

    Funder
    Australian Research Council
    Funding Amount
    $215,000.00
    Summary
    Design surface feature recognition for near net shaped manufactured components. The aim of this project is to investigate methods and techniques that, given an ab initio design requirement, allow databases of knowledge from previous designs to be intelligently searched for similar patterns, both geometric and physical state, that will assess the likelihood of a successful design and suggest potential alternatives based on previous experience The plan is to approach the research problem from a m .... Design surface feature recognition for near net shaped manufactured components. The aim of this project is to investigate methods and techniques that, given an ab initio design requirement, allow databases of knowledge from previous designs to be intelligently searched for similar patterns, both geometric and physical state, that will assess the likelihood of a successful design and suggest potential alternatives based on previous experience The plan is to approach the research problem from a machine learning/pattern recognition point of view. By mapping the characterized properties into a search space of reduced dimensionality in which feature patterns have been pre-classified through supervised training, it should be possible to identify similar features.
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    Funded Activity

    Discovery Projects - Grant ID: DP0346541

    Funder
    Australian Research Council
    Funding Amount
    $167,213.00
    Summary
    Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It takes significant skills to configure systems properly such that they are safe from malicious attacks. The proposed project aims at designing automatic systems which are able to adapt to an existing network configuration and which detect novel and unusual events. For this purpose we will use modern machine learning techniques, mainly based on kernels. In particular, rec .... Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It takes significant skills to configure systems properly such that they are safe from malicious attacks. The proposed project aims at designing automatic systems which are able to adapt to an existing network configuration and which detect novel and unusual events. For this purpose we will use modern machine learning techniques, mainly based on kernels. In particular, recently developed algorithms to estimate the support of a distribution and detect rare events will be employed in this context. The project is in cooperation with Dr. Ralf Herbrich (Microsoft Research, Cambridge).
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    Funded Activity

    Discovery Projects - Grant ID: DP0877635

    Funder
    Australian Research Council
    Funding Amount
    $245,000.00
    Summary
    Foundations and Architectures for Agent Systems. Computer systems are now involved in many aspects of everyday life, commerce, and industry. Making these systems more intelligent has thus become a priority research issue. Agents systems, with their emphasis on autonomy, proactiveness, reactivity, and sociability, are widely regarded as a crucial technology for realising the capabilities that computer systems will need over the next few decades. The proposed research aims to make some fundamenta .... Foundations and Architectures for Agent Systems. Computer systems are now involved in many aspects of everyday life, commerce, and industry. Making these systems more intelligent has thus become a priority research issue. Agents systems, with their emphasis on autonomy, proactiveness, reactivity, and sociability, are widely regarded as a crucial technology for realising the capabilities that computer systems will need over the next few decades. The proposed research aims to make some fundamental contributions to agent systems that will be used to build future computer systems that will have an even more profound positive impact on everyday life, commerce and industry than existing systems.
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    Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347079

    Funder
    Australian Research Council
    Funding Amount
    $160,000.00
    Summary
    Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufact .... Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufacturing - in particular sheet metal components for the automotive industry. The facilities will enable a database of dimensional and strain information to be established in support of related manufacturing R&D projects.
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