Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100235
Funder
Australian Research Council
Funding Amount
$280,000.00
Summary
Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure wil ....Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure will accelerate the pace of surveillance research and development in Australia, enhancing the competitiveness of both Australia's researchers and the businesses that will commercialise these researchers' discoveries.Read moreRead less
Tracking targets in large scale surveillance camera networks. The research is expected to provide a significant boost in the effectiveness of safety and security measures for public facilities and open spaces that are monitored by surveillance cameras. The general public benefits from this through a decreased need for intrusive security measures, and increased deterrence of crime and anti-social behaviour. This capability is in demand worldwide for both public and private camera networks, whose ....Tracking targets in large scale surveillance camera networks. The research is expected to provide a significant boost in the effectiveness of safety and security measures for public facilities and open spaces that are monitored by surveillance cameras. The general public benefits from this through a decreased need for intrusive security measures, and increased deterrence of crime and anti-social behaviour. This capability is in demand worldwide for both public and private camera networks, whose usefulness is currently limited by the difficulty of monitoring them. We therefore anticipate considerable commercial interest in Australia and internationally.
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Strengthening the evidence: how community-based Indigenous health and wellbeing interventions work to improve policy and practice. Indigenous Australians suffer high rates of premature morbidity and mortality. Despite the need for programs to improve Indigenous health and wellbeing, there is little evidence to indicate which community-based programs are effective and why they are effective. This research program addresses this 'need-evidence' gap to inform policy and practice.
Image search for simulator content creation. The World Wide Web contains tens of billions of images, with personal and industrial collections stretching to may times that number. The potential economic value of these image-based resources is enormous, but largely untapped as we have no practical way of recovering the images we need. This project will develop image search technologies which will allow Australian industry to exploit these important resources. Some of the wide variety of possible ....Image search for simulator content creation. The World Wide Web contains tens of billions of images, with personal and industrial collections stretching to may times that number. The potential economic value of these image-based resources is enormous, but largely untapped as we have no practical way of recovering the images we need. This project will develop image search technologies which will allow Australian industry to exploit these important resources. Some of the wide variety of possible applications might include the searching of surveillance video for objects of interest, vision-based guidance of unmanned vehicles, smart-phone and smart-home systems which understand their environments, and stock tracking systems which can detect spoilage.Read moreRead less
Planning for a better life under the National Disability Insurance Scheme (NDIS). This project aims to analyse and define the experiences and expectations of people with disability in rural and remote regions. People accessing the National Disability Insurance Scheme (NDIS) are required to complete a personalised service plan, however despite these reforms, people in rural and remote communities currently experience many challenges with the scheme. Using qualitative research methods, the project ....Planning for a better life under the National Disability Insurance Scheme (NDIS). This project aims to analyse and define the experiences and expectations of people with disability in rural and remote regions. People accessing the National Disability Insurance Scheme (NDIS) are required to complete a personalised service plan, however despite these reforms, people in rural and remote communities currently experience many challenges with the scheme. Using qualitative research methods, the project will investigate people’s experiences engaging with Local Area Coordinators and Planners under the Rural and Remote Strategy 2016-2019 and Aboriginal and Torres Strait Islander Engagement Strategy. The project will provide significant outcomes for Aboriginal and non-Aboriginal people with disability in rural and remote areas, disability service providers, and government and non-government policy makers.Read moreRead less
Remote Aboriginal families and carers of children with disabilities. The project intends to explore the challenges that Aboriginal families who have children with disabilities experience when living in remote communities. Living in a community with family supports is important for the wellbeing, health and spirituality of Aboriginal people in the Ngaanyatjarra Pitjantjara Yankunytjatjara (NPY) lands. However, the NPY Women’s Council are concerned that this is a significant challenge for families ....Remote Aboriginal families and carers of children with disabilities. The project intends to explore the challenges that Aboriginal families who have children with disabilities experience when living in remote communities. Living in a community with family supports is important for the wellbeing, health and spirituality of Aboriginal people in the Ngaanyatjarra Pitjantjara Yankunytjatjara (NPY) lands. However, the NPY Women’s Council are concerned that this is a significant challenge for families and carers of children with disabilities. Project results will be used to propose models for supporting children with disabilities and their families and caregivers to live good lives in their communities. The outcomes are expected to inform service redesign to allow Aboriginal people to fully benefit from the National Disability Insurance Scheme.Read moreRead less
Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-im ....Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-image understanding cannot be tackled similarly because the number of possible combinations of objects is too large. The project thus proposes a graph-based generalisation of the CNN approach which allows scene structure to be learned explicitly. This would represent an important step towards providing computers with robust vision, allowing them to interact with their environment.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170101259
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Zero-shot and few-shot learning with deep knowledge transfer. This project aims to develop few-shot and zero-shot learning, visual recognition techniques that can learn a visual concept with few or no visual examples. Visual recognition is a major component in Artificial Intelligence and used in cybernetic security, robotic vision and medical image analysis. This project will use deep learning to enable the zero/few-shot learning to use and model previously unexplored information, making zero/fe ....Zero-shot and few-shot learning with deep knowledge transfer. This project aims to develop few-shot and zero-shot learning, visual recognition techniques that can learn a visual concept with few or no visual examples. Visual recognition is a major component in Artificial Intelligence and used in cybernetic security, robotic vision and medical image analysis. This project will use deep learning to enable the zero/few-shot learning to use and model previously unexplored information, making zero/few-shot learning more practical, scalable and flexible. The project is expected to advance the applicability of visual recognition in many challenging scenarios and provide effective tools to analyse the online visual data for supporting Australia’s cybernetic security.Read moreRead less
Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the ....Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the primary limitations of deep learning and will greatly increase its practical application to a range of industrial, cultural or health settings.Read moreRead less
Added depth: automated high level image interpretation. Humans are very good at understanding the world through imagery, but computers lack this fundamental capacity because they lack experience of what they might see. This project will provide this experience by combining the large volumes of imagery on the Internet with three dimensional information generated by humans for other purposes.