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
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
Teaching Software Agents to Play. This project is fundamental to computational intelligence and human brain science. Both strongly impact on the community and the nation. They form the backbone of contemporary information science and are key to our National Research Priorities. This research is of great community benefit. Our results will enable everyone to rapidly search, analyse and interpret vast amounts of information that is irretrievable by current methods. They will also enliven interacti ....Teaching Software Agents to Play. This project is fundamental to computational intelligence and human brain science. Both strongly impact on the community and the nation. They form the backbone of contemporary information science and are key to our National Research Priorities. This research is of great community benefit. Our results will enable everyone to rapidly search, analyse and interpret vast amounts of information that is irretrievable by current methods. They will also enliven interactive entertainment by spontaneously creating unique, tailor-made music. In sum, we are making a leap forward in the crucial area of collaborative intelligence.Read moreRead less
Evolving largest scale concept structures. This project will find new methods of collective intelligence- many small computer programs acting in synergy. Such software has many applications from data mining to networks of sensors, but the main focus will be on one of the Grand Challenges of artificial intelligence -- the Japanese game of Go. Go is at least as difficult as Chess but computers are far from reaching the skill of human experts. Insights into the human brain from autism and savants w ....Evolving largest scale concept structures. This project will find new methods of collective intelligence- many small computer programs acting in synergy. Such software has many applications from data mining to networks of sensors, but the main focus will be on one of the Grand Challenges of artificial intelligence -- the Japanese game of Go. Go is at least as difficult as Chess but computers are far from reaching the skill of human experts. Insights into the human brain from autism and savants will form the foundations of the new computational approaches we will develop.Read moreRead less
Reconceiving Machine Learning. The proposed research will develop a new way to consider problems to which machine learning can be applied. Machine learning is crucial enabler of the digital economy. The research will provide better opportunities for Australian industry to gain a competitive advantage with machine learning technology. The framework developed will enable better opportunities for collaborative research and will build and strengthen international linkages.
A more intelligent knowledge-based system apprentice. Our previous techniques already had an impact on Australian industry, with five Australian companies marketing such technology, and for three of these it is a central technology. We expect an early uptake of the enhancements we propose by these companies, greatly increasing their international competitiveness against other rule technologies. Three of these companies are very recent, so we would expect other company uptake of the new enhance ....A more intelligent knowledge-based system apprentice. Our previous techniques already had an impact on Australian industry, with five Australian companies marketing such technology, and for three of these it is a central technology. We expect an early uptake of the enhancements we propose by these companies, greatly increasing their international competitiveness against other rule technologies. Three of these companies are very recent, so we would expect other company uptake of the new enhanced technology. In turn Australian companies using the technology will improve their competitiveness in an increasingly knowledge-based economy by being able to more rapidly and easily deploy knowledge-based systems. Our previous techniques have already had a significant impact in medical practice.Read moreRead less
Emergency Control of Catastrophic Disturbances in a Power System. Following the tragic events of 11 September 2001, there are increased concerns about the security and robustness of power systems to evolving spectra of threats, such as natural disasters (e.g., earthquakes and hurricanes), equipment failure, human error, or deliberate sabotage and attack by terrorists. In this project, pattern recognition of local parameter changes in distributed monitoring systems will be used to identify any th ....Emergency Control of Catastrophic Disturbances in a Power System. Following the tragic events of 11 September 2001, there are increased concerns about the security and robustness of power systems to evolving spectra of threats, such as natural disasters (e.g., earthquakes and hurricanes), equipment failure, human error, or deliberate sabotage and attack by terrorists. In this project, pattern recognition of local parameter changes in distributed monitoring systems will be used to identify any threatened breakdown in the power system. Once identified, methods based on intelligent agents will be used to trigger the appropriate countermeasures to maintain the integrity of transmission grids.Read moreRead less
A Novel System for Surveillance of Moving Objects. Surveillance of moving objects is critical in numerous applications such as detection and recognition of motor vehicles. It is important for detection to be fast and accurate with low cost. In this project, we aim to implement a surveillance system consisting of an efficient algorithm on a PC network with a camera. Our detection algorithm will be achieved with an advanced and computationally powerful image representation for fast computation. It ....A Novel System for Surveillance of Moving Objects. Surveillance of moving objects is critical in numerous applications such as detection and recognition of motor vehicles. It is important for detection to be fast and accurate with low cost. In this project, we aim to implement a surveillance system consisting of an efficient algorithm on a PC network with a camera. Our detection algorithm will be achieved with an advanced and computationally powerful image representation for fast computation. Its accuracy will be enhanced by adapting a well recognized theory for fast removal of image noise. Our implementation on the PC network will provide a flexible and extensible platform for parallel computing to further reduce detection time while keeping costs low.Read moreRead less
Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of profi ....Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of proficiency testing and continuing education vital for a vibrant, well regulated discipline. In addition, the project will contribute to our knowledge of the pathology assessed in the screening and diagnosis of cancers such as cervical, lung and bladder cancers.Read moreRead less