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Research Topic : Intelligent Robotics
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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 Training Centres - Grant ID: IC190100017

    Funder
    Australian Research Council
    Funding Amount
    $3,703,664.00
    Summary
    ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource .... ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource attributes, maximising value ‘on the fly’. Benefits will include increasing certainty on product quality and maximising throughput and recovery. Outcomes will include new tools to rapidly model geological and geometallurgical uncertainty with sensor inputs, to track the resource to product and enhance interpretation.
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    Showing 1-2 of 2 Funded Activites

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