Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-vi ....Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-visual services that are of great interest to international standards bodies and industry, while facilitating free interaction and augmented reality. This project will provide significant benefits to broadcast, entertainment, surveillance and health industries and position Australia as a world leader in this field.Read moreRead less
Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored ....Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored to individual characteristics. The success of this project could significantly advance the fundamental research in image analysis. Expected outcomes include new knowledge and algorithms for image analysis, which could benefit fields like biology and archaeology, where labeled images are hard to attain and scarce.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100057
Funder
Australian Research Council
Funding Amount
$339,446.00
Summary
Creating tactile electronic books for people with vision impairment. This project aims to create a framework which allows authoring, reading and storing of tactile electronic books for people with vision impairment by using multi-touch, audio, and tactile technologies. The project expects to generate new knowledge in the areas of human computer interaction and information visualisation utilising new techniques to present visual information in the form of audio and tactile. Expected outcomes of t ....Creating tactile electronic books for people with vision impairment. This project aims to create a framework which allows authoring, reading and storing of tactile electronic books for people with vision impairment by using multi-touch, audio, and tactile technologies. The project expects to generate new knowledge in the areas of human computer interaction and information visualisation utilising new techniques to present visual information in the form of audio and tactile. Expected outcomes of the project are to reduce the cost of authoring accessible textual and graphical content, and to provide a practical and intuitive reading experience. This should provide benefits to people with vision impairment while accessing information in a more effective and efficient way.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101402
Funder
Australian Research Council
Funding Amount
$415,000.00
Summary
Multi-scale, multi-modal X-ray imaging using speckle. This project aims to develop new X-ray imaging methods that capture multiple next-generation image modalities at an unprecedented range of length and time scales. While conventional X-ray imaging is routinely used in medicine and industry, it can only visualise high-density materials like bone. To reveal low-density objects like biological soft tissue and microstructure like tiny cracks, the project plans to extract two complementary image mo ....Multi-scale, multi-modal X-ray imaging using speckle. This project aims to develop new X-ray imaging methods that capture multiple next-generation image modalities at an unprecedented range of length and time scales. While conventional X-ray imaging is routinely used in medicine and industry, it can only visualise high-density materials like bone. To reveal low-density objects like biological soft tissue and microstructure like tiny cracks, the project plans to extract two complementary image modalities using a robust setup that does not rely on large-scale facilities. Significant benefits from the developed methods are expected for leading-edge research in fields including biomedicine, materials science and palaeontology, and industries such as security, medical diagnostics and manufacturing.Read moreRead less
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