Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0561231
Funder
Australian Research Council
Funding Amount
$671,715.00
Summary
MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools acc ....MRI GRID Computing Facility: Design, Optimisation and Image Processing. The MRI Grid Computing Facility provides the IT infrastructure to achieve effective e-research in the area of magnetic resonance (MR) imaging, a field of neuroscience research that revolutionizes the way brain diseases are identified and treated. The facility consists of a dedicated high performance grid compute engine, distributed visualisation workstations, and distributed data warehouse facilities. Software tools accessible through the Internet will enable researchers to archive, retrieve and exchange data and software; access distributed MR image databases and the latest MR image analysis tools; schedule analysis tasks on the grid compute engine, the outcomes of which will be visualized by the visualization workstations.Read moreRead less
Special Research Initiatives - Grant ID: SR0567334
Funder
Australian Research Council
Funding Amount
$125,748.00
Summary
A Grid-Enabled National Archive of Nanostructural Imagery (GRANI). The Nanostructural Analysis Network Organization (NANO) is an Australian Major National Research Facility that provides access to a grid of advanced microscopic instruments for the nanostructural analysis of both physical materials and biological systems. The aim of this initiative is to provide the NANO community with a set of common, interoperable tools and services to enable more efficient, cost-effective storage, management, ....A Grid-Enabled National Archive of Nanostructural Imagery (GRANI). The Nanostructural Analysis Network Organization (NANO) is an Australian Major National Research Facility that provides access to a grid of advanced microscopic instruments for the nanostructural analysis of both physical materials and biological systems. The aim of this initiative is to provide the NANO community with a set of common, interoperable tools and services to enable more efficient, cost-effective storage, management, analysis and sharing of generated microscopic images, video and analytical data. The significance of the proposed middleware is that it will improve collaboration and reduce duplication across many disciplines, through a shareable, distributed national scientific image/video database.Read moreRead less
Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than ai ....Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than aiming to achieve invariance to it. The project will also research new data agnostic feature compaction capabilities to enable scalable learning on the world’s largest and challenging expression dataset available to us through international collaboration. Tackling these two major open problems will make accurate coding of facial expressions in natural environments achievable.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130101775
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Distributed large-scale optimisation methods in computer vision. With the number of images and video available over the internet reaching billions and growing, the need for new tools for handling and interpreting such huge amounts of data is quickly becoming apparent. This project will focus on developing new optimisation methods for efficiently computing solutions for a broad class of large-scale problems.
Progressive Transmission of Street Directory Assistance and Business Pages over 3G and 4G mobile networks. Multimedia on-demand and live services over 3G and 4G mobiles will be enhanced. New methods for low volume, high information transfer multimedia transactions will be developed. This will create new jobs in the Information and Communication Technologies (ICT) sector. Progressive transmission of street directory assistance and business pages information to mobile handsets will enable citize ....Progressive Transmission of Street Directory Assistance and Business Pages over 3G and 4G mobile networks. Multimedia on-demand and live services over 3G and 4G mobiles will be enhanced. New methods for low volume, high information transfer multimedia transactions will be developed. This will create new jobs in the Information and Communication Technologies (ICT) sector. Progressive transmission of street directory assistance and business pages information to mobile handsets will enable citizens to make efficient use of their time and improve productivity. The 3G and 4G cellular telephone network, extended with 'mobile' base stations and satellite links, are especially attractive to a large country like Australia. Interactive information retrieval will become more universal and not limited through wired Internet connections.
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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.
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
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
Omniscient face recognition for uncooperative subjects. The outcomes of this project will enable effective video surveillance technology to be developed for use by law enforcement and national security agencies. It will lead to reliable identification of humans at a distance by automatically detecting and recognising faces, for use in counter-terrorism surveillance and commercial robot-human interfaces.
High resolution single particle analysis of biological macromolecules. One of the great challenges of cell biology is to increase the rate of atomic resolution structure determination, particularly of membrane proteins and macromolecular assemblies. The current rate-limiting step is high quality crystal production. Our goal is to prove that protein structures can be determined to atomic resolution by single-particle analysis. 3D structures will be produced by computationally aligning high-resolu ....High resolution single particle analysis of biological macromolecules. One of the great challenges of cell biology is to increase the rate of atomic resolution structure determination, particularly of membrane proteins and macromolecular assemblies. The current rate-limiting step is high quality crystal production. Our goal is to prove that protein structures can be determined to atomic resolution by single-particle analysis. 3D structures will be produced by computationally aligning high-resolution electron microscope images of individual, randomly oriented molecules. The importance of this project is highlighted by the fact over 120,000 protein sequences are already databased, a number set to increase rapidly as new genome sequencing projects are completed.
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