Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, includ ....Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, including relational learning, with human-assisted knowledge acquisition methods. The expected outcomes will be new techniques for image understanding, particularly for our test domain, namely, High Resolution Computed Tomography scans of the lung.Read moreRead less
Adaptation of Vision Model to Perceptual Digital Picture Compression. This project spearheads research in the next generation digital picture compression technology, placing Australia an undisputed leader in this area of frontier technology. It will generate intellectual property and software prototype systems, which can be readily transferred into a vast number of visual communication and service applications, feeding into and rejuvenating national high-tech industries. These applications incl ....Adaptation of Vision Model to Perceptual Digital Picture Compression. This project spearheads research in the next generation digital picture compression technology, placing Australia an undisputed leader in this area of frontier technology. It will generate intellectual property and software prototype systems, which can be readily transferred into a vast number of visual communication and service applications, feeding into and rejuvenating national high-tech industries. These applications include digital photography for fine art, medical imaging, picture archive and communication systems for telemedicine and rural health care systems, high quality digital picture, video and cinematic experience, crime prevention, border control, security and surveillance systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170100037
Funder
Australian Research Council
Funding Amount
$329,287.00
Summary
Time series classification for new-generation Earth observation satellites. This project aims to develop time series classification methods for satellite images, to produce accurate temporal land-cover maps. Latest generation satellites have just begun imaging Earth frequently, completely, in high-resolution, and at no charge to end-users – an unprecedented opportunity to monitor the flux of our planet's systems. However, time series classification techniques do not scale to handle such wealth o ....Time series classification for new-generation Earth observation satellites. This project aims to develop time series classification methods for satellite images, to produce accurate temporal land-cover maps. Latest generation satellites have just begun imaging Earth frequently, completely, in high-resolution, and at no charge to end-users – an unprecedented opportunity to monitor the flux of our planet's systems. However, time series classification techniques do not scale to handle such wealth of data. The project anticipates its time series technologies will be applicable in agriculture planning, fire prevention, and disaster mapping, and that substantially greater value can be derived from significant investments into Earth Observation programmes.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120101778
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Building change detection and map update using multispectral imagery and height data. This project will produce an effective building change detection procedure and a digital building map. Automatic building detection assists in taking possible precautions during natural disasters, whilst automatic building change detection facilitates an effective and efficient management of affected areas during and after the calamity.
Autonomous service robots in a multi-agent based system for household and industrial environments. This project addresses fundamental research issues required to develop autonomous mobile robots for intelligent cleaning services. As an interdisciplinary project spanning the fields of robotics, mechatronics and AI, it offers potential benefits in bringing robots into less-structured human environments. Robots performing autonomous cleaning (including hazardous waste and spillage) and security tas ....Autonomous service robots in a multi-agent based system for household and industrial environments. This project addresses fundamental research issues required to develop autonomous mobile robots for intelligent cleaning services. As an interdisciplinary project spanning the fields of robotics, mechatronics and AI, it offers potential benefits in bringing robots into less-structured human environments. Robots performing autonomous cleaning (including hazardous waste and spillage) and security tasks in both household and industrial environments has tremendous national/community benefits in cost and time savings, improved efficiency and safety, and facilitating hazardous or labour intensive tasks. Other benefits include research training, strengthening Australia's R&D position in key innovative technologies, and creating jobs and exports.Read moreRead less
An integrated model for assessing health effects of nanoparticle inhalation. This project aims to examine the associated risks of nanoparticle inhalation on heath by developing a toxicological predictive tool for health risk assessment. The outcomes of this research will lead to greatly improved preventative measures, thereby reducing occupational diseases and the health socio-economic burden of Australia.
A Multiscale Modelling Platform for Nanoparticle Inhalation Risk Assessment. This project aims to explore the health risks caused by nanoparticle inhalation and its penetration through respiratory mucus and tissue cells. Exposure to nanoparticles has the potential to cause serious and possibly fatal health effects. An understanding of nanoparticle toxicology would enable us to appropriately protect the public’s health and safety. The project plans to consider human respiratory anatomy and physio ....A Multiscale Modelling Platform for Nanoparticle Inhalation Risk Assessment. This project aims to explore the health risks caused by nanoparticle inhalation and its penetration through respiratory mucus and tissue cells. Exposure to nanoparticles has the potential to cause serious and possibly fatal health effects. An understanding of nanoparticle toxicology would enable us to appropriately protect the public’s health and safety. The project plans to consider human respiratory anatomy and physiology and use advanced computer modelling and experimental techniques to evaluate the health risk of exposure to the burgeoning number of nanomaterials found in consumer products. The expected outcome of the project is a predictive tool that determines nanoparticle exposure risk and its health consequences.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100660
Funder
Australian Research Council
Funding Amount
$358,731.00
Summary
Simulating social networks to understand how neighbourhood factors influence health. Where you live and who you know has implications for your health. This study will use social network models to understand how social characteristics of neighbourhoods influence health. The new insights gained will help policy makers to develop better strategies for reducing health inequalities and improving health outcomes.
Modelling the Development and Evolution of Business Relations and Networks as Complex Adaptive Systems using Agent Based Models. This research develops models that will allow managers and policy makers to play more effective roles in the development and evolution of collaborative business relations and networks that lead to greater efficiency, industry innovation, and firm competitiveness, which is a key focus of corporate management and government trade and industry policy. It will also enhance ....Modelling the Development and Evolution of Business Relations and Networks as Complex Adaptive Systems using Agent Based Models. This research develops models that will allow managers and policy makers to play more effective roles in the development and evolution of collaborative business relations and networks that lead to greater efficiency, industry innovation, and firm competitiveness, which is a key focus of corporate management and government trade and industry policy. It will also enhance Australia's resources and expertise in understanding and modelling complex adaptive systems, help develop education resources and training programs for practitioners and researchers in this fast growing area of theory and research, strengthen links with leading researchers and centres, and produce a doctorate in the area.Read moreRead less
Reshaping superannuation practice in Australia using big data analytics. This project aims to reform superannuation investment practices in Australia. Using sophisticated data analytics and machine-learning techniques, combined with economic modelling and quantitative finance. The project will try to understand the broad characteristics of Australian superannuation investors and their practice from a ‘big data’ perspective. The expected outcomes of this project are the identification of key dete ....Reshaping superannuation practice in Australia using big data analytics. This project aims to reform superannuation investment practices in Australia. Using sophisticated data analytics and machine-learning techniques, combined with economic modelling and quantitative finance. The project will try to understand the broad characteristics of Australian superannuation investors and their practice from a ‘big data’ perspective. The expected outcomes of this project are the identification of key determinants for successful superannuation behaviour to inform decision-making for better superannuation practices and policies. It is expected that the insights arising from this project will contribute to safeguarding the future of Australia’s superannuation schemes, and to better financial security at retirement.Read moreRead less