Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0775582
Funder
Australian Research Council
Funding Amount
$530,000.00
Summary
Data Grid -- Access Layer. Vast increases in computing power and the arrival of new scientific instruments are contributing to the so-called data deluge of the 21st century. Accessing and archiving these data is essential to research. While the underlying computing and network requirements are well resourced, data access has been relatively neglected in Australia. A continuing problem in Australian research communities is the absence of coordinated access to digital storage resources. In many ca ....Data Grid -- Access Layer. Vast increases in computing power and the arrival of new scientific instruments are contributing to the so-called data deluge of the 21st century. Accessing and archiving these data is essential to research. While the underlying computing and network requirements are well resourced, data access has been relatively neglected in Australia. A continuing problem in Australian research communities is the absence of coordinated access to digital storage resources. In many cases computational and experimental data are stored on ad-hoc resources, such as local university servers, PC disc drives, and are not generally accessible. The central goal of this proposal is to provide access to an integrated scientific data storage capacity for Australia.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0668445
Funder
Australian Research Council
Funding Amount
$800,000.00
Summary
Data Grid Storage Infrastructure for e-Research. Vast increases in computing power and the arrival of new scientific instruments are contributing to the so-called data deluge of the 21st century. Archiving these data is essential to research. While the underlying computing and network requirements are well resourced, data storage capacity has been relatively neglected in Australia. A continuing problem in Australian research communities is the absence of coordinated digital storage resources. In ....Data Grid Storage Infrastructure for e-Research. Vast increases in computing power and the arrival of new scientific instruments are contributing to the so-called data deluge of the 21st century. Archiving these data is essential to research. While the underlying computing and network requirements are well resourced, data storage capacity has been relatively neglected in Australia. A continuing problem in Australian research communities is the absence of coordinated digital storage resources. In many cases computational and experimental data are stored on ad-hoc resources, such as local university servers, PC disc drives, CDs, or DVDs, and are not generally accessible. The central goal of this proposal is to provide a long-term, integrated scientific data storage capacity for Australia. Read moreRead less
Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior ....Pattern Recognition and Scene Analysis via Machine Learning. We plan to use kernel methods, a novel machine learning technique, for computer vision problems, such as scene analysis and real time object recognition. Such capabilities are relevant for the design of intelligent and adaptive systems, suitable for complex real world environments. Expected outcomes are the design of efficient statistical tools which take the special nature of visual data into account (structure, decomposition, prior knowledge of physical environments, etc.) and combine the advantages of feature based high-level vision methods with low-level machine learning techniques.
This proposal is part of a joint IST project with partners from the European Union.Read moreRead less
Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, ....Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.Read moreRead less
Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help securi ....Generic Content-based News Picture Retrieval with Local Invariant Features. Image Retrieval searches for images from large databases whose visual content meets the requirements submitted by users. Besides directly benefiting the Partner Organization, this project will enable more efficient access to large picture repositories in news agencies and publishers, digital libraries and film archives. It will make public use of visual information much more convenient and economical. It will help security officers to effortlessly and accurately find particular scenes from the images generated by a large closed-circuit TV networks. Also, the developed technology can be applied to tele-education and e-commerce. New algorithms developed in this project will benefit the Australian and world scientific communities.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347407
Funder
Australian Research Council
Funding Amount
$100,000.00
Summary
Infrastructure for wireless Internet technology development for rural Australia. Three nodes of a low-power, very-high frequency digital wireless network will be installed at two locations in the Australian National University and one location at the University of Canberra. An additional node will then be located a further distance away (> 50 kms) in the ACT. This network will allow the development of novel technology for moderate speed (>100 kbps) non-line of sight wireless Internet access o ....Infrastructure for wireless Internet technology development for rural Australia. Three nodes of a low-power, very-high frequency digital wireless network will be installed at two locations in the Australian National University and one location at the University of Canberra. An additional node will then be located a further distance away (> 50 kms) in the ACT. This network will allow the development of novel technology for moderate speed (>100 kbps) non-line of sight wireless Internet access over ranges of 3-100 km for potential use by regional Australian Internet providers. The network will also catalyse research and training in wireless communication technology , digital signal processing, and computer networking.Read moreRead less