Web-based Multimedia Information Management System For Use In Remote Diagnosis Of Eye Diseases
Funder
National Health and Medical Research Council
Funding Amount
$196,000.00
Summary
Our aim is to develop a web-based multimedia information management system for use in remote diagnosis of eye diseases. The proposed system will provide medical advice and diagnosis, information and distance education for those working in health care as well as the community, computer-aided diagnosis and assistance in the operational and medical decision-making process. Less expensive health care personnel should be able to use the system with little training in remote and rural areas. Significa ....Our aim is to develop a web-based multimedia information management system for use in remote diagnosis of eye diseases. The proposed system will provide medical advice and diagnosis, information and distance education for those working in health care as well as the community, computer-aided diagnosis and assistance in the operational and medical decision-making process. Less expensive health care personnel should be able to use the system with little training in remote and rural areas. Significantly, the project should empower remote general doctors and nurses by proper access to expert advice, save many remote patients from unnecessary visits to specialist centres on the one hand and allow more proper diagnosis and intervention on the other. It has the potential for significant reductions in the cost of health care delivery, should strengthening the bond between medical services in remote and city areas, provide training and education of local GPs, nurses, health care workers and optometrists and provide web-based disease management systems will provide instant access to health care information. The outcomes of this project are potentially of great significance to remote and rural communities in Australia and around the world. There will be an enormous impact on current health care practices. Significantly, the project should empower remote general doctors and nurses by proper access to expert advice, save many remote patients from unnecessary visits to specialist centres on the one hand and allow more proper diagnosis and intervention on the other. It has the potential for significant reductions in the cost of health care delivery, should strengthening the bond between medical services in remote and city areas, provide training and education of local GPs, nurses, health care workers and optometrists and provide web-based disease management systems will provide instant access to health care information. The outcomes of this project are potentially of great significance to remote and rural communities in Australia and around the world. There will be an enormous impact on current health care practices.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0668542
Funder
Australian Research Council
Funding Amount
$425,000.00
Summary
Multimedia Computing, Production, Management and Distribution for HDTV and its Applications. Australia is the first country to launch digital TV nationally. Increasingly, this platform will be used for consuming multimedia information; also the HDTV infrastructure is being applied to other domains such as telemedicine/e-Health to lower costs and improve effectiveness. For Australia to be a step ahead in the development of these applications that are beneficial to a wider community, we have to lo ....Multimedia Computing, Production, Management and Distribution for HDTV and its Applications. Australia is the first country to launch digital TV nationally. Increasingly, this platform will be used for consuming multimedia information; also the HDTV infrastructure is being applied to other domains such as telemedicine/e-Health to lower costs and improve effectiveness. For Australia to be a step ahead in the development of these applications that are beneficial to a wider community, we have to look forward and establish adequate infrastructure for the development of needed applications of the future. It is strongly believed that by doing so we can position ourselves ahead of other communities in anticipating and providing essential services to our modern society and this in turn will greatly benefit the Australian economy.Read moreRead less
Special Research Initiatives - Grant ID: SR0354584
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
ARC Research Network in Multimedia Technology and Applications (MTA). Multimedia Information Technology is becoming a major stream for modern computers, networks, and new platforms (e.g. embedded-systems, mobile-phones, PDAs, digital-TV) in various applications, including media production and e-healthcare where Australia has tremendous strengths. This proposal aims to bring top researchers in the related areas, including IT, Healthcare, Architecture and Visual-arts, to push a new technological w ....ARC Research Network in Multimedia Technology and Applications (MTA). Multimedia Information Technology is becoming a major stream for modern computers, networks, and new platforms (e.g. embedded-systems, mobile-phones, PDAs, digital-TV) in various applications, including media production and e-healthcare where Australia has tremendous strengths. This proposal aims to bring top researchers in the related areas, including IT, Healthcare, Architecture and Visual-arts, to push a new technological wave in Australia, to provide its value promised to Australian business, and to take international leadership in multimedia computing. Its outcome includes the formation of research teams, coordinated by a board, for 10 programs, and a CSCW-system & related website to facilitate the group work.Read moreRead less
Application Frameworks for Collaborative Learning. We will pioneer the use of key software engineering techniques - design patterns and application frameworks - to reduce the cost and improve the quality of online collaborative learning activities. For the first time, we will combine software engineering and educational knowledge to use design patterns to describe best practice for these activities in engineering terms; we will use application frameworks to aggregate these patterns and implement ....Application Frameworks for Collaborative Learning. We will pioneer the use of key software engineering techniques - design patterns and application frameworks - to reduce the cost and improve the quality of online collaborative learning activities. For the first time, we will combine software engineering and educational knowledge to use design patterns to describe best practice for these activities in engineering terms; we will use application frameworks to aggregate these patterns and implement them as a readily usable tool. The result will be a powerful new generation of stable collaborative eLearning tools with enhanced scalability, interoperability and adaptability.Read moreRead less
Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop ....Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop efficient privacy preserving algorithms to deal with static and dynamic network data sharing. The success of this project will benefit many industries and government agencies to reduce users’ privacy breaches, avoid illegal consequences of sharing data, and enhance these service providers’ service quality.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100200
Funder
Australian Research Council
Funding Amount
$428,847.00
Summary
Cohesive Multipartite Subgraph Discovery in Large Heterogeneous Networks. This project aims to devise novel cohesive multipartite subgraph models and corresponding efficient search algorithms based on various applications. Significant advances in understanding big data will be enabled by the proposed novel theories and algorithms, which can leverage the value of heterogeneous network data and serve as the foundation of network analytics. Expected outcomes of this project include novel cohesive m ....Cohesive Multipartite Subgraph Discovery in Large Heterogeneous Networks. This project aims to devise novel cohesive multipartite subgraph models and corresponding efficient search algorithms based on various applications. Significant advances in understanding big data will be enabled by the proposed novel theories and algorithms, which can leverage the value of heterogeneous network data and serve as the foundation of network analytics. Expected outcomes of this project include novel cohesive multipartite subgraph models, efficient searching algorithms and platforms for heterogeneous networks. This should provide significant benefits for different organisations and a myriad of applications dealing with heterogeneous network data, including but not limited to e-commerce, cybersecurity, health and social networks.Read moreRead less
Fast Reconstruction and Real-time Rendering of Immersive Light Field Video. This project aims to develop new learning-based methods for reconstructing and rendering 3D immersive videos from multi-view 2D videos. The project expects to generate new knowledge in the areas of data mining, multimedia, pattern recognition and deep learning. Expected outcomes of this project include new deep neural networks to represent 3D videos, neural methods for high-fidelity video rendering and efficient 3D video ....Fast Reconstruction and Real-time Rendering of Immersive Light Field Video. This project aims to develop new learning-based methods for reconstructing and rendering 3D immersive videos from multi-view 2D videos. The project expects to generate new knowledge in the areas of data mining, multimedia, pattern recognition and deep learning. Expected outcomes of this project include new deep neural networks to represent 3D videos, neural methods for high-fidelity video rendering and efficient 3D video reconstruction and rendering algorithms. This should provide significant benefits to a diverse range of practical applications, such as autonomous driving, virtual reality, healthcare, advanced manufacturing, and many other 3D applications.Read moreRead less
Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a n ....Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a new data management and processing foundation for big video data analytics.Read moreRead less
Big temporal graph processing in the Cloud. This project aims to develop efficient and scalable algorithms to process big temporal graphs in the Cloud. In particular, we will investigate three most representative types of queries over big temporal graphs including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big temporal graphs as well as a system prototype for evaluation ....Big temporal graph processing in the Cloud. This project aims to develop efficient and scalable algorithms to process big temporal graphs in the Cloud. In particular, we will investigate three most representative types of queries over big temporal graphs including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and road networks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100668
Funder
Australian Research Council
Funding Amount
$435,000.00
Summary
Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations ....Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big streaming temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and social analysis.Read moreRead less