Advanced Interface Technologies for Computational Science & Simulation. The project will research novel computer vision technologies that enable the next generation of visualisation portals for scientific collaboration. The development of new computer vision tools is key to truly natural human-machine interaction. The research outcomes of this project directly align with National Research Priority 3: Frontier Technologies. It supports four of the five relevant priority goals - Breakthrough Scien ....Advanced Interface Technologies for Computational Science & Simulation. The project will research novel computer vision technologies that enable the next generation of visualisation portals for scientific collaboration. The development of new computer vision tools is key to truly natural human-machine interaction. The research outcomes of this project directly align with National Research Priority 3: Frontier Technologies. It supports four of the five relevant priority goals - Breakthrough Science, Frontier Technologies, Smart Information Use, and Promoting an Innovation Culture and Economy. Outcomes of this research are also relevant to Research Priority 4: Safeguarding Australia, and has direct applications to video surveillance technology. Significant commercial opportunities, including licensing and spin-offs exist.Read moreRead less
Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, rec ....Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, recently
developed algorithms to estimate the support of a distribution and
detect rare events will be employed in this context.
The project is in cooperation with Dr. Ralf Herbrich (Microsoft
Research, Cambridge).
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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
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
Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a ....Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.Read moreRead less
ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, ....ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, semi autonomous wheelchairs), and civil disaster support (eg. fighting bushfires, looking for people in rubble) always keeping people in the loop so that strong human/ machine cooperative ventures can achieve what neither human or machines could accomplish independently.Read moreRead less