AUSLearn: AUtomated Sample Learning for Object Recognition. This project aims to enable computers to learn how to effectively use training samples for object recognition. Training sample is the only source used by computers to learn recognising objects. This project creates a new research direction that will enable the first full exploration of the power of samples. The aims will be enabled by leveraging the recent advances in reinforcement learning, fast training algorithms, and by developing n ....AUSLearn: AUtomated Sample Learning for Object Recognition. This project aims to enable computers to learn how to effectively use training samples for object recognition. Training sample is the only source used by computers to learn recognising objects. This project creates a new research direction that will enable the first full exploration of the power of samples. The aims will be enabled by leveraging the recent advances in reinforcement learning, fast training algorithms, and by developing novel deep learning algorithms. The new algorithms will benefit a wide range of applications, e.g. to effectively use car crash training samples for accurately identifying potential road crashes in transport and to effectively use rare medical imaging training data for robustly diagnosing diseases in health.Read moreRead less
Coach My Ride: Mentorable Interfaces to support Older Australians' Mobility. This project aims to co-design new interfaces to support older Australians to collaboratively learn the use of automated vehicles. We will seek to understand the needs, expectations, and challenges of urban and rural residents, and the peer support strategies they deploy to learn technology. Mobility is key to the wellbeing of older people, but automated vehicles that are too complex will fail to deliver their promise o ....Coach My Ride: Mentorable Interfaces to support Older Australians' Mobility. This project aims to co-design new interfaces to support older Australians to collaboratively learn the use of automated vehicles. We will seek to understand the needs, expectations, and challenges of urban and rural residents, and the peer support strategies they deploy to learn technology. Mobility is key to the wellbeing of older people, but automated vehicles that are too complex will fail to deliver their promise of independent ageing. Outcomes will be a new theory of collaborative learning and new mentorable interfaces to allow older adults to mentor each other to access and use new mobility solutions. This will contribute to narrow the digital and mobility gap improving the independence, safety and wellbeing of ageing Australians.Read moreRead less
Visual field impairment and injury: A population-based study. This project aims to link a large-scale ophthalmic database of visual field tests to population-based injury data which includes police-reported crash data, hospitalisation, death and trauma data in people aged over 60 years. The identification of individuals with high risk visual fields will enable the development of targeted interventions at the local, national and international level to prevent injuries due to visual field loss. Si ....Visual field impairment and injury: A population-based study. This project aims to link a large-scale ophthalmic database of visual field tests to population-based injury data which includes police-reported crash data, hospitalisation, death and trauma data in people aged over 60 years. The identification of individuals with high risk visual fields will enable the development of targeted interventions at the local, national and international level to prevent injuries due to visual field loss. Significant benefits include a reduction in the number of injuries and consequent reductions in personal harm and health care demands.Read moreRead less