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

    Discovery Projects - Grant ID: DP0879814

    Funder
    Australian Research Council
    Funding Amount
    $220,000.00
    Summary
    Mixture models for high-dimensional clustering with applications to tumour classification, network intrusion, and text classification. This project will benefit the Australian Society as a whole by developing statistical methodology for the clustering of high-dimensional data. In particular, it will develop a novel and efficient model for extracting useful information from subpopulations. It thus has wide applicability to improving the quality and validity of applied research in most industries .... Mixture models for high-dimensional clustering with applications to tumour classification, network intrusion, and text classification. This project will benefit the Australian Society as a whole by developing statistical methodology for the clustering of high-dimensional data. In particular, it will develop a novel and efficient model for extracting useful information from subpopulations. It thus has wide applicability to improving the quality and validity of applied research in most industries in Australia. More specifically, it is to be applied here to classify brain tumours and detect network intruders. This cross-disciplinary project will contribute to Australia's economic of public health, protect Australia from crime, and strength Australian researchers' capacity and capability of participating in this emerging science.
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    Funded Activity

    Discovery Projects - Grant ID: DP0557387

    Funder
    Australian Research Council
    Funding Amount
    $162,000.00
    Summary
    Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financi .... Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financial transactions. The technology will also assist in the protection of the community and safeguard Australia by enabling the implementation of the following: suspect identification using voice print; national security measures for combating terrorism by using voice to locate and track terrorists; preemptive criminal activity counter-measures; surveillance and secure building access by voice.
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    Funded Activity

    Discovery Projects - Grant ID: DP0879250

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive .... Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive and specific detection of early cancers, the potential reductions in morbidity and mortality from breast cancer will be of immense value. Successful implementation of the proposed project will further enhance Australia's position as a world leader in biomedical research and application of computational technologies to health problems.
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    Funded Activity

    Discovery Projects - Grant ID: DP0451129

    Funder
    Australian Research Council
    Funding Amount
    $195,000.00
    Summary
    Privacy Preserving Data Mining as Autonomous Data Analysis Expands into Safeguarding from Threats like Crime and Terrorism. In a world characterized by digitally coded data, Data Mining allows automatic exploration of huge numbers of personal records for target marketing, as well as demographic, medical and criminal research. Investigations into terrorist attacks use this technology, but a balance with privacy protection is necessary. Even if names and unique identifiers are removed, computer me .... Privacy Preserving Data Mining as Autonomous Data Analysis Expands into Safeguarding from Threats like Crime and Terrorism. In a world characterized by digitally coded data, Data Mining allows automatic exploration of huge numbers of personal records for target marketing, as well as demographic, medical and criminal research. Investigations into terrorist attacks use this technology, but a balance with privacy protection is necessary. Even if names and unique identifiers are removed, computer methods can be used to infer confidential information about individuals. This project develops new techniques to ensure privacy and alleviate public concerns such as secondary use of personal data. We shall develop new methods for replacing original data with data that exhibits approximately the same patterns, but conceals sensitive data.
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    Funded Activity

    Discovery Projects - Grant ID: DP0877929

    Funder
    Australian Research Council
    Funding Amount
    $196,000.00
    Summary
    Feature-Level Fusion with Incomplete Data for Automatic Person Identification. This research addresses the current key problems in automated person recognition with incomplete data using multiple traits. The outcomes of this research will not only make a significant contribution to fundamental theory but also result in a wide range of crime and terrorism preventing applications including police database searching, access control, security monitoring and surveillance. They can be used either by p .... Feature-Level Fusion with Incomplete Data for Automatic Person Identification. This research addresses the current key problems in automated person recognition with incomplete data using multiple traits. The outcomes of this research will not only make a significant contribution to fundamental theory but also result in a wide range of crime and terrorism preventing applications including police database searching, access control, security monitoring and surveillance. They can be used either by police and law enforcement agencies, or at places of airport, government buildings, military facilities and even sensitive areas in offices and factories. It will help reduce crime, enhance the security of the nation to a world-advanced level, and generate new industry and export opportunities for Australian security industry.
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    Funded Activity

    Discovery Projects - Grant ID: DP0774601

    Funder
    Australian Research Council
    Funding Amount
    $170,000.00
    Summary
    RadioGenes2: Modelling complex biomolecular interactions in radiated tumours: Towards understanding the genesis of therapeutic radioresistance. About 45% of bladder cancer patients require radiotherapy or surgery. Radiotherapy has a failure rate of ~50%. Surgery (bladder removal) diminishes quality of life considerably. Modelling complex gene interactions in radiated cancer cells will provide crucial knowledge on the molecular genesis of radiotherapy-resistance of tumours. Our findings will prov .... RadioGenes2: Modelling complex biomolecular interactions in radiated tumours: Towards understanding the genesis of therapeutic radioresistance. About 45% of bladder cancer patients require radiotherapy or surgery. Radiotherapy has a failure rate of ~50%. Surgery (bladder removal) diminishes quality of life considerably. Modelling complex gene interactions in radiated cancer cells will provide crucial knowledge on the molecular genesis of radiotherapy-resistance of tumours. Our findings will provide: (i) an accurate mathematical/computational model for diagnosing radiosensitivity; (ii) further insights to be applied in the pharmaceutical sector such as the discovery of novel molecular targets that have the potential to increase radiotherapy success ratios; (iii) a holistic modelling technique applicable to a larger diversity of tumours.
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    Funded Activity

    Discovery Projects - Grant ID: DP0451091

    Funder
    Australian Research Council
    Funding Amount
    $165,000.00
    Summary
    Face recognition under varying pose and lighting--towards automatic personal identification for surveillance systems. One of the key remaining problems in computerized human face recognition is the need to handle the variability in appearance due to changes in pose. This proposed research targets at identifying a person with a face image in a pose different from the example view by using a novel texture analysis and synthesis technique. This technique makes use of facial textures at different vi .... Face recognition under varying pose and lighting--towards automatic personal identification for surveillance systems. One of the key remaining problems in computerized human face recognition is the need to handle the variability in appearance due to changes in pose. This proposed research targets at identifying a person with a face image in a pose different from the example view by using a novel texture analysis and synthesis technique. This technique makes use of facial textures at different viewing directions and can recover appropriate textures for virtual views in arbitrary poses. The successfulness of the proposed research would make a technical breakthrough towards solving the major remaining problem in face recognition.
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    Funded Activity

    Discovery Projects - Grant ID: DP0345901

    Funder
    Australian Research Council
    Funding Amount
    $165,000.00
    Summary
    Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discove .... Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.
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    Funded Activity

    Discovery Projects - Grant ID: DP0877835

    Funder
    Australian Research Council
    Funding Amount
    $195,000.00
    Summary
    Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security meas .... Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security measures for combating terrorism by using voice to locate and track terrorists. Our research at QUT Speech Research Lab is at the forefront of development in this field and will provide Australia with a technological advantage in the rapidly evolving global market for speaker recognition technology for person authentication applications.
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    Funded Activity

    Discovery Projects - Grant ID: DP0772887

    Funder
    Australian Research Council
    Funding Amount
    $895,099.00
    Summary
    Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most .... Multivariate Methods for the Analysis of Microarray Gene-Expression Data with Applications to Cancer Diagnostics. The project will benefit the Australian Society as a whole by developing statistical methodology for the analysis of high-throughput data. In particular, it will develop a novel and easily implemented model for the analysis of correlated and structured data that may be of high dimension. It thus has wide applicability to improving the quality and validity of applied research in most industries in Australia. More specifically, it is to be applied here to the diagnosis and prognosis of ovarian cancer. This cross-disciplinary project will strengthen Australian researchers' capacity and capability of participating in cutting-edge DNA microarray research.
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