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Australian State/Territory : VIC
Research Topic : intelligence
Field of Research : Signal Processing
Status : Closed
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  • Researchers (18)
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  • Funded Activity

    Linkage Projects - Grant ID: LP0349046

    Funder
    Australian Research Council
    Funding Amount
    $209,139.00
    Summary
    Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techn .... Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techniques using concepts of dynamic sensor scheduling and stochastic control to provide computationally feasible and near optimal solutions to the limited and varying bandwidth problem. This work will greatly enhance the operational performance of distributed sensor networks.
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    Funded Activity

    Discovery Projects - Grant ID: DP0210359

    Funder
    Australian Research Council
    Funding Amount
    $181,084.00
    Summary
    Advanced Sonar Sensing for Robotics. Robotics research is heavily dependent on fast, accurate, reliable and cheap sensors. Sonar sensing can fulfil these requirements in air and underwater environments. This project will advance this sensor technology by providing sonar with high-speed accurate measurement and classification capabilities that function on moving platforms. The sonar will adapt and monitor differing environmental conditions allowing the sensor data to be integrated better with .... Advanced Sonar Sensing for Robotics. Robotics research is heavily dependent on fast, accurate, reliable and cheap sensors. Sonar sensing can fulfil these requirements in air and underwater environments. This project will advance this sensor technology by providing sonar with high-speed accurate measurement and classification capabilities that function on moving platforms. The sonar will adapt and monitor differing environmental conditions allowing the sensor data to be integrated better with other sensors, such as laser and stereo vision. Interference rejection will be incorporated that will allow the sensor to operate in conjunction with other sonar. Applications of the technology will be robotic mapping, localisation, navigation and exploration.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT130101394

    Funder
    Australian Research Council
    Funding Amount
    $606,740.00
    Summary
    Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in bi .... Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in biomedical image analysis. This project will lead to fundamental contributions as well as techniques that address both problems: extraction of relevant features information from multisubject brain imaging data sets of the same modality or from fusion of brain imaging data sets collected from multimodalities.
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    Funded Activity

    Discovery Projects - Grant ID: DP150104645

    Funder
    Australian Research Council
    Funding Amount
    $370,100.00
    Summary
    Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vecto .... Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vector conversion methods. It is expected to develop a framework where semantic labels and hyperlinks can be embedded in visual data automatically. It hopes to pioneer the creation of a web of images where the links are on image/video regions. New image simplification, stylisation, and non-photorealistic rendering methods are expected to be provided.
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