ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, ....ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, semi autonomous wheelchairs), and civil disaster support (eg. fighting bushfires, looking for people in rubble) always keeping people in the loop so that strong human/ machine cooperative ventures can achieve what neither human or machines could accomplish independently.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101058
Funder
Australian Research Council
Funding Amount
$437,254.00
Summary
Glass-box Deep Machine Perception for Trustworthy Artificial Intelligence. Explainability and Transparency are the key values for development and deployment of Artificial Intelligence (AI) in Australia’s AI Ethics Framework for industry and governments. This project aims to build new tools to make the central technology of AI - deep learning - transparent and explainable. Its expected outputs are novel theory-driven algorithms and unconventional foundational blocks for deep learning that will al ....Glass-box Deep Machine Perception for Trustworthy Artificial Intelligence. Explainability and Transparency are the key values for development and deployment of Artificial Intelligence (AI) in Australia’s AI Ethics Framework for industry and governments. This project aims to build new tools to make the central technology of AI - deep learning - transparent and explainable. Its expected outputs are novel theory-driven algorithms and unconventional foundational blocks for deep learning that will allow humans to clearly interpret the reasoning process of this technology, which is currently not possible. It is expected to significantly advance our knowledge in machine intelligence and perception. Due to their fundamental nature, the project outcomes are likely to benefit industry and scientific frontiers alike.Read moreRead less
Assistive technologies for Autism support. Growing numbers of children are diagnosed with Autism Spectrum Disorder, leading to a massive financial burden on educational, medical and social service systems. This project aims to construct technological solutions to ease this cost with software frameworks for both children and parents. These novel tools and techniques address key issues: personalisation of early intervention, extension of interventions in alternate contexts, and parental support th ....Assistive technologies for Autism support. Growing numbers of children are diagnosed with Autism Spectrum Disorder, leading to a massive financial burden on educational, medical and social service systems. This project aims to construct technological solutions to ease this cost with software frameworks for both children and parents. These novel tools and techniques address key issues: personalisation of early intervention, extension of interventions in alternate contexts, and parental support through analysis of social media. The outcomes aim to include algorithms and prototype applications for flexible early intervention and support for parents and carers, including evaluation of the developed tools in real-world settings.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.Read moreRead less
Computational tools to analyse and exploit the social media revolution. We aim to create technologies to analyse social media communities, which are rapidly growing in reach, complexity, and content produced and shared. Powerful techniques to tap this resource will lead to commercial outcomes for marketing and search industries, alongside deeper insight into the cultural and social impact of this Internet revolution.
A theoretical framework for practical partial fingerprint identification. Fingerprints captured from a crime scene are often partial and poor quality which makes it difficult to identify the criminal suspects from large databases. This project will find mathematical models which can estimate the missing information located in the blank areas of a partial fingerprint and effectively identify it.
Accuracy and cost-effectiveness of technology-assisted dietary assessment. This project aims to compare leading methods for technology-assisted dietary assessment. Excessive cost and questionable accuracy limit the routine use of dietary assessment and undermine decision making in Australia. This project intends to compare three technology methods of assessing diet with the current standard recall method used in population surveys in order to confirm if the use of food images and automated metho ....Accuracy and cost-effectiveness of technology-assisted dietary assessment. This project aims to compare leading methods for technology-assisted dietary assessment. Excessive cost and questionable accuracy limit the routine use of dietary assessment and undermine decision making in Australia. This project intends to compare three technology methods of assessing diet with the current standard recall method used in population surveys in order to confirm if the use of food images and automated methods provide new approaches to improve accuracy and consumer acceptability. Expected outcomes of this project include more accurate and acceptable methods of assessing dietary intake. These findings will inform decision making for researchers, policy makers and practitioners in Australia, and potentially lead to more regular population surveillance.Read moreRead less