Data Management Technologies for the Magnetic Resonance Imaging e-Research Grid. Howard Florey Institute researchers will collaborate with SGI's file-systems engineering team. Substantial benefits are expected from the development of techniques to support centralized and distributed processing medical image datasets. Issues requiring research include file space allocation algorithms and caching strategies. The proposed rapid database access technologies aim at solving these problems in the medic ....Data Management Technologies for the Magnetic Resonance Imaging e-Research Grid. Howard Florey Institute researchers will collaborate with SGI's file-systems engineering team. Substantial benefits are expected from the development of techniques to support centralized and distributed processing medical image datasets. Issues requiring research include file space allocation algorithms and caching strategies. The proposed rapid database access technologies aim at solving these problems in the medical imaging research context. The project attempts to 'improve data management for existing and new business applications'. This enhanced sharing of information will improve critical mass therefore fostering national and international collaboration. Read moreRead less
Semantic Authentication of Visual Data. Data authentication systems can detect the smallest modification to a message. Authentication systems for media objects such as images, and audio and video clips have a different requirement they must ensure authenticity of the content without needing all the changes to be detectable. The aims of this project are to develop a framework for design and analysis of image and video authentication systems, and construct secure and flexible systems that can be ....Semantic Authentication of Visual Data. Data authentication systems can detect the smallest modification to a message. Authentication systems for media objects such as images, and audio and video clips have a different requirement they must ensure authenticity of the content without needing all the changes to be detectable. The aims of this project are to develop a framework for design and analysis of image and video authentication systems, and construct secure and flexible systems that can be used in practice. This research addresses the urgent need of providing security for multimedia objects in electronic commerce and is of high importance to the acceptance of advanced communication and information services.Read moreRead less
Robust and scalable change detection in geo-spatial data. A flood of data in the form of text, images and video emanate from a proliferation of sensors. These data are collected but rarely analysed, rendering it meaningless. This project aims to develop new software and techniques to detect changes over time in large scale geographically referenced data (for example photomaps) for use across numerous domains.
Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emer ....Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.Read moreRead less
Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new appr ....Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new approach to digital video coding other than the constant bit rate coding techniques which have dominated digital video research for the past four decades. It will form a part of the theoretical foundation and principles for the next generation video coding and compression techniques, and may lead to new standards and practice.Read moreRead less
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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The Circus Oz Living Archive: developing a model of online digital engagement for the performing arts. The performing arts play a crucial role in defining our national identity. Circus Oz, as a flagbearer of contemporary Australian cultural identity around the globe, shares the challenges faced by the sector, including increasing competition for audiences and changing expectations about the relationship between audiences and creative content. Cultural dialogue and creative activity increasingly ....The Circus Oz Living Archive: developing a model of online digital engagement for the performing arts. The performing arts play a crucial role in defining our national identity. Circus Oz, as a flagbearer of contemporary Australian cultural identity around the globe, shares the challenges faced by the sector, including increasing competition for audiences and changing expectations about the relationship between audiences and creative content. Cultural dialogue and creative activity increasingly occur online. The performing arts need to explore novel ways to deepen online community engagement to strengthen their artform. This project researches how digital technologies can help the performing arts employ their documented cultural heritage to drive innovations in repertoire development, performance scholarship and audience interaction.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
A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medi ....A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medicine, which recognises that there are important differences between individuals with a particular disease, and that when patients are separated into sub-populations with similar disease patterns, treatment can be tailored to these sub-populations.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