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
Ensembles of Collaborative Neural Networks. Artificial neural networks have been used successfully for data mining and control. A neural network ensemble(NNE) is a collection of networks that exhibits properties of self-organization, plasticity, and adaptive behaviour. The aim of this research is to develop an efficient and theoretically sound algorithm for NNE learning. The outcomes of the project will include insights into self-organization of complex NNE and automatic problem decomposition an ....Ensembles of Collaborative Neural Networks. Artificial neural networks have been used successfully for data mining and control. A neural network ensemble(NNE) is a collection of networks that exhibits properties of self-organization, plasticity, and adaptive behaviour. The aim of this research is to develop an efficient and theoretically sound algorithm for NNE learning. The outcomes of the project will include insights into self-organization of complex NNE and automatic problem decomposition and an efficient algorithm for constructing and training NNE. Practical outcomes will include research training for early career researchers and new modelling tools for data mining, robotics and multi-agent systems. The project contributes to the national priority area of smart information use.Read moreRead less
Automatic detection of the circle of Willis in neuro-images using multi-scale gradient calculation and knowledge-based genetic algorithms. Stroke is the third most common cause of death and a major contributor to long term disability in Australia. The most efficient way of preventing stroke from happening is to detect related symptoms early. The group of cerebral blood vessels that closely related to strokes is the circle of Willis (CoW). We build a system that can automatically detect and quan ....Automatic detection of the circle of Willis in neuro-images using multi-scale gradient calculation and knowledge-based genetic algorithms. Stroke is the third most common cause of death and a major contributor to long term disability in Australia. The most efficient way of preventing stroke from happening is to detect related symptoms early. The group of cerebral blood vessels that closely related to strokes is the circle of Willis (CoW). We build a system that can automatically detect and quantify CoW in neuroimages, providing ways of preventing strokes from happening. The project will enhance Australia¡¯s leading position in promoting and maintaining good health, especially in preventive healthcare.Read moreRead less
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less
Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected ....Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected outcomes include the
development of software that allows the solution of hitherto unsolved machine
learning problems, and the ability to solve problems larger than those solvable
by the current generation of machine learning tools.Read moreRead less
Internet web page mining. This project aims to study the behaviour of internet search engines designed using a best first search strategy, and to improve on the existing designs. The outcome of the project will be a much better design of internet search engine which can be used to search for specific topics. The benefit to the Australian partner will be the gaining of skills in internet search engine design, originating from the Italian partner's group. The benefit to the Italian partner will be ....Internet web page mining. This project aims to study the behaviour of internet search engines designed using a best first search strategy, and to improve on the existing designs. The outcome of the project will be a much better design of internet search engine which can be used to search for specific topics. The benefit to the Australian partner will be the gaining of skills in internet search engine design, originating from the Italian partner's group. The benefit to the Italian partner will be the gaining of skills in research techniques, e.g., utilising a support vector machine as a classification tool, data mining techniques developed originally by the Australian partner's group, and in further developments of these techniques with specific applications to the internet web page mining problem.Read moreRead less
Extensions to the page scoring algorithm in internet search engine studies. This project proposes to study two extensions to the Page rank equation which is one of the theoretical underpinning of Google's web page scoring engine. In particular, we wish to explore ways to combine page connectivity and page characteristics in the scoring of web pages. This will be the first time a rational way is proposed for combining these two factors. The expected outcome will be a deeper understanding on how t ....Extensions to the page scoring algorithm in internet search engine studies. This project proposes to study two extensions to the Page rank equation which is one of the theoretical underpinning of Google's web page scoring engine. In particular, we wish to explore ways to combine page connectivity and page characteristics in the scoring of web pages. This will be the first time a rational way is proposed for combining these two factors. The expected outcome will be a deeper understanding on how these two factors affect the scores of a web page in a search engine, and hence how they affect the visibility of the page in response to a query.
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Data structures which change with time, a machine learning approach. Visibility of web pages, based on page importance, on the Internet controls their accessibility by users which is critical for e-Commerce applications. The page importance depends on its contents and its link structure to other web pages, both of which can be time varying. This project proposes a novel model in which time varying aspects of the changes to contents and their link structures are captured, thus allowing us a bette ....Data structures which change with time, a machine learning approach. Visibility of web pages, based on page importance, on the Internet controls their accessibility by users which is critical for e-Commerce applications. The page importance depends on its contents and its link structure to other web pages, both of which can be time varying. This project proposes a novel model in which time varying aspects of the changes to contents and their link structures are captured, thus allowing us a better understanding of how these influence the page importance over time. It will also allow us insight on how to improve the visibility of web pages.Read moreRead less
Investigations in Learning Algorithms for Web Page Scoring Systems. Modification of web page scores to satisfy requirements, e.g., one page should have a higher page score than another, a home page should have higher score than any other pages in the same site, using modifications of the forcing function, and the link connectivity matrix respectively of the PageRank equation will be studied. By clustering web pages either by ranks or by scores will help overcome issues of scale and complexity wh ....Investigations in Learning Algorithms for Web Page Scoring Systems. Modification of web page scores to satisfy requirements, e.g., one page should have a higher page score than another, a home page should have higher score than any other pages in the same site, using modifications of the forcing function, and the link connectivity matrix respectively of the PageRank equation will be studied. By clustering web pages either by ranks or by scores will help overcome issues of scale and complexity which are required for the live world wide web. Outcomes will provide a rational basis together with practical methods for modifying web page scores by a web site administrator.Read moreRead less
Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis f ....Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis for the development of platform technology capable of monitoring and detection of neural health status. Success is expected to yield a new generation of smart dynamic non-invasive systems that will be critical for developing effective solutions to counter life threating conditions for a large cross section of the Australian population.Read moreRead less