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Current Selection
Scheme : Discovery Projects
Field of Research : Pattern Recognition
Australian State/Territory : VIC
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  • Funded Activity

    Discovery Projects - Grant ID: DP0666456

    Funder
    Australian Research Council
    Funding Amount
    $168,000.00
    Summary
    Pattern-Based Video Coding Techniques for Real-Time Low Bit-Rate and Low Complexity Encoding Applications. This project will benefit the National Research Priority on Frontier Technology with applications in video surveillance, smart home design, and patient monitoring. It will enable Australia to lead the world in setting up coding standards and thus impact directly on the manufacturing initiatives of the multimedia communication and entertainment industries. Telecommunication industries will b .... Pattern-Based Video Coding Techniques for Real-Time Low Bit-Rate and Low Complexity Encoding Applications. This project will benefit the National Research Priority on Frontier Technology with applications in video surveillance, smart home design, and patient monitoring. It will enable Australia to lead the world in setting up coding standards and thus impact directly on the manufacturing initiatives of the multimedia communication and entertainment industries. Telecommunication industries will be the immediate beneficiary by enabling quality live video transmissions at low bit rates in a cost-effective manner. This project will improve the ability of large organisations to operate virtually across huge distances in Australia with the aid of reliable multimedia communications using distributed devices of limited power and processing capacity.
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    Funded Activity

    Discovery Projects - Grant ID: DP1093233

    Funder
    Australian Research Council
    Funding Amount
    $310,000.00
    Summary
    Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being .... Surviving the data deluge: Scalable feature extraction, discrimination and analysis for computer vision tasks using compressed sensed data. Strategically, our pioneering solutions besides being technically and socially significant, open fresh options for sensor-agnostic data analysis. The technical significance lies through the creation of new technologies for the critical national and global security markets, currently overwhelmed by data. The social significance arises from our solutions being privacy preserving, providing new avenues for the production of novel, socially acceptable products for aged care monitoring. Our methods spearhead future advancement in diverse disciplines due to the wide applicability of the methods to other sensor networks (Square Kilometre Array) and data types, providing new frameworks for addressing crucial problems of data management.
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    Funded Activity

    Discovery Projects - Grant ID: DP0211972

    Funder
    Australian Research Council
    Funding Amount
    $50,000.00
    Summary
    Adaptive learning of spatiotemporal patterns: Development of multi-layer spiking neuron networks using Hebbian and competitive learning. The aim of this project is to develop a method for recognising patterns that change in time. The development of a reliable method that is fast and robust to noise will have wide application in many areas, especially computer speech recognition where timing plays a crucial role. Building-blocks similar to those in the brain (spiking neurons) will be used. Aut .... Adaptive learning of spatiotemporal patterns: Development of multi-layer spiking neuron networks using Hebbian and competitive learning. The aim of this project is to develop a method for recognising patterns that change in time. The development of a reliable method that is fast and robust to noise will have wide application in many areas, especially computer speech recognition where timing plays a crucial role. Building-blocks similar to those in the brain (spiking neurons) will be used. Automatic techniques will be used to teach groups of spiking neurons the differences between sequences of events by adjusting connections between them. The significance of this approach is that it captures information about timing that is missed in existing techniques.
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    Funded Activity

    Discovery Projects - Grant ID: DP0878801

    Funder
    Australian Research Council
    Funding Amount
    $422,000.00
    Summary
    Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those .... Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those people and vehicles are doing), industrial prototyping and inspection (measuring the size and shape of objects), urban planning (laser scanning streetscapes to create computer models of cities), entertainment industry (movie special effects and games), etc.
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    Funded Activity

    Discovery Projects - Grant ID: DP0987421

    Funder
    Australian Research Council
    Funding Amount
    $245,000.00
    Summary
    Automatic Human Age Estimation Based on Visual Information. Age verification is important for many security applications including passport control for border security, and protecting children from adult websites, venues, or products. Accurate, reliable and practical age estimation or verification technologies would be of enormous benefit for 'Safeguarding Australia'. The ability of a machine to estimate a person's age and provide an age-appropriate interface also has benefits for the young and .... Automatic Human Age Estimation Based on Visual Information. Age verification is important for many security applications including passport control for border security, and protecting children from adult websites, venues, or products. Accurate, reliable and practical age estimation or verification technologies would be of enormous benefit for 'Safeguarding Australia'. The ability of a machine to estimate a person's age and provide an age-appropriate interface also has benefits for the young and old in our society. The outcome of this project, practical technologies for automatic human age estimation based on visual information, will dramatically change the current (non-technology based) methods of age verification and create new opportunities for customised human-machine interfaces.
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    Funded Activity

    Discovery Projects - Grant ID: DP0453249

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Pattern Recognition and Interpretation in Sequence Data. With the recent advances in sequencing technology, the amount of biological sequence data available has increased tremendously. Extraction of knowledge from such data has lagged behind, awaiting the development of new automated methods for extracting meaning from the sequences. This project aims to develop fast and flexible algorithms for discovery of patterns in DNA and protein sequence data and to find families of sequences that share si .... Pattern Recognition and Interpretation in Sequence Data. With the recent advances in sequencing technology, the amount of biological sequence data available has increased tremendously. Extraction of knowledge from such data has lagged behind, awaiting the development of new automated methods for extracting meaning from the sequences. This project aims to develop fast and flexible algorithms for discovery of patterns in DNA and protein sequence data and to find families of sequences that share similar patterns. Association of these patterns with features of 3-dimensional structures of protein families and their functional characteristics can contribute towards the understanding of the relationship between primary structure and function of a protein.
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    Funded Activity

    Discovery Projects - Grant ID: DP0771183

    Funder
    Australian Research Council
    Funding Amount
    $249,000.00
    Summary
    Computational techniques for protease research. Protease research is an area of intensive research in Australia. Correctly assessing the mechanisms of protease function is crucial not only for improving our health through medical research and drug development, but also to multiple national areas of research and development, including biotechnology, agriculture, and industries such as the dairy industry. This project will develop innovative computational techniques to advance understanding of h .... Computational techniques for protease research. Protease research is an area of intensive research in Australia. Correctly assessing the mechanisms of protease function is crucial not only for improving our health through medical research and drug development, but also to multiple national areas of research and development, including biotechnology, agriculture, and industries such as the dairy industry. This project will develop innovative computational techniques to advance understanding of how proteases function by redressing a common research assumption that can significantly affect the accuracy of protease function prediction. The outcomes will improve fundamental research into proteases, and enable improved research and development in the many fields that rely on protease work.
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    Funded Activity

    Discovery Projects - Grant ID: DP0453205

    Funder
    Australian Research Council
    Funding Amount
    $150,000.00
    Summary
    Adaptive learning in networks of spiking neurons for recognising patterns that change with time. The aim of this project is to develop a method for recognising patterns that change with time. Building-blocks similar to those in the brain (spiking neurons) will be used. Automatic techniques will be developed to teach groups of spiking neurons the differences between sequences of events by adjusting connections between neurons. The significance of this approach is that it captures information abou .... Adaptive learning in networks of spiking neurons for recognising patterns that change with time. The aim of this project is to develop a method for recognising patterns that change with time. Building-blocks similar to those in the brain (spiking neurons) will be used. Automatic techniques will be developed to teach groups of spiking neurons the differences between sequences of events by adjusting connections between neurons. The significance of this approach is that it captures information about timing that is missed in existing techniques. The development of a reliable method that is fast and robust to noise will have wide application in many areas, especially computer speech recognition where timing plays a crucial role.
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    Funded Activity

    Discovery Projects - Grant ID: DP0771815

    Funder
    Australian Research Council
    Funding Amount
    $225,000.00
    Summary
    Temporal Pattern Learning and Recognition in Neural Systems. This project is relevant to the National Research Priority area of Frontier Technologies and addresses fundamental cross-disciplinary issues of how neural systems learn patterns that change with time, which is at the cutting edge of intelligent processing systems. Applications are in rapidly growing fields of automatic speech processing, robotics, machine learning and intelligent systems, all with applications in areas of economic impo .... Temporal Pattern Learning and Recognition in Neural Systems. This project is relevant to the National Research Priority area of Frontier Technologies and addresses fundamental cross-disciplinary issues of how neural systems learn patterns that change with time, which is at the cutting edge of intelligent processing systems. Applications are in rapidly growing fields of automatic speech processing, robotics, machine learning and intelligent systems, all with applications in areas of economic importance. Application to cochlear implant speech processing will provide benefit for the hearing impaired. The project will provide students with training at an international level within Australia, thus helping ensure Australia maintains and extends its science and technology base into the future.
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    Funded Activity

    Discovery Projects - Grant ID: DP1096699

    Funder
    Australian Research Council
    Funding Amount
    $185,000.00
    Summary
    Understanding cortical processing: Neuronal activity and learning in recurrently connected networks. This project addresses fundamental cross-disciplinary issues of information processing and control in large-scale biological neural systems. This is an area of research that is at the cutting edge of intelligent processing systems. An understanding of these mechanisms would have considerable implications in areas that span a range of complex biological and artificial neural systems, including the .... Understanding cortical processing: Neuronal activity and learning in recurrently connected networks. This project addresses fundamental cross-disciplinary issues of information processing and control in large-scale biological neural systems. This is an area of research that is at the cutting edge of intelligent processing systems. An understanding of these mechanisms would have considerable implications in areas that span a range of complex biological and artificial neural systems, including the rapidly growing fields of robotics, machine learning, and adaptive control, all with applications in diverse areas of economic importance. The project will provide students with training at an international level within Australia, thus helping ensure Australia maintains and extends its science and technology base.
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