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Field of Research : Pattern Recognition
Research Topic : PROCESSING
Australian State/Territory : NSW
Australian State/Territory : ACT
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  • Funded Activity

    Discovery Projects - Grant ID: DP1095725

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Reconceiving Machine Learning. The proposed research will develop a new way to consider problems to which machine learning can be applied. Machine learning is crucial enabler of the digital economy. The research will provide better opportunities for Australian industry to gain a competitive advantage with machine learning technology. The framework developed will enable better opportunities for collaborative research and will build and strengthen international linkages.
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    Funded Activity

    Discovery Projects - Grant ID: DP0343346

    Funder
    Australian Research Council
    Funding Amount
    $159,264.00
    Summary
    Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori .... Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.
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    Funded Activity

    Linkage Projects - Grant ID: LP0991757

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help securi .... Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help security officers to effortlessly and accurately find particular scenes from the images generated by a large closed-circuit TV networks. Also, the developed technology can be applied to tele-education and e-commerce. New algorithms developed in this project will benefit the Australian and world scientific communities.
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    Funded Activity

    Discovery Projects - Grant ID: DP0208969

    Funder
    Australian Research Council
    Funding Amount
    $258,752.00
    Summary
    Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing the ideas of large margins and kernels have attracted much attention lately because of their impressive performance on real world problems such as optical character recognition. We plan to refine and extend such algorithms to a wide range of different machine learning problems such as gene sequence analysis, image processing and text classification. Expected .... Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing the ideas of large margins and kernels have attracted much attention lately because of their impressive performance on real world problems such as optical character recognition. We plan to refine and extend such algorithms to a wide range of different machine learning problems such as gene sequence analysis, image processing and text classification. Expected outcomes include the development of software that allows the solution of hitherto unsolved machine learning problems, and the ability to solve problems larger than those solvable by the current generation of machine learning tools.
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    Funded Activity

    Discovery Projects - Grant ID: DP0774054

    Funder
    Australian Research Council
    Funding Amount
    $263,993.00
    Summary
    Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a .... Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.
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    Showing 1-5 of 5 Funded Activites

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