A hardware accellerated platform for high-fidelity, high speed simulation of infrared scenes. Missiles present a major military and terrorist threat to aircraft and ships. A possible method to detect them is an infrared imaging system which is sensitive to a missile's spectrally unique rocket propulsion exhaust. It is both dangerous and expensive to conduct field trials; so simulation is used extensively. This project aims to use high performance computing to accelerate the slowest parts of the ....A hardware accellerated platform for high-fidelity, high speed simulation of infrared scenes. Missiles present a major military and terrorist threat to aircraft and ships. A possible method to detect them is an infrared imaging system which is sensitive to a missile's spectrally unique rocket propulsion exhaust. It is both dangerous and expensive to conduct field trials; so simulation is used extensively. This project aims to use high performance computing to accelerate the slowest parts of the industrial partner's existing simulations: the generation of simulated infrared images.
This project will improve the competitiveness of the manufacturer of infrared threat and warning systems and provide research training in an area of high performance computing.
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Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-im ....Whole image understanding by convolutions on graphs. This project seeks to develop technologies that will help computer vision interpret the whole visible scene, rather than just some of the objects therein. Existing automated methods for understanding images perform well at recognising specific objects in canonical poses, but the problem of whole image interpretation is far more challenging. Convolutional neural networks (CNN) have underpinned recent progress in object recognition, but whole-image understanding cannot be tackled similarly because the number of possible combinations of objects is too large. The project thus proposes a graph-based generalisation of the CNN approach which allows scene structure to be learned explicitly. This would represent an important step towards providing computers with robust vision, allowing them to interact with their environment.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170101259
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Zero-shot and few-shot learning with deep knowledge transfer. This project aims to develop few-shot and zero-shot learning, visual recognition techniques that can learn a visual concept with few or no visual examples. Visual recognition is a major component in Artificial Intelligence and used in cybernetic security, robotic vision and medical image analysis. This project will use deep learning to enable the zero/few-shot learning to use and model previously unexplored information, making zero/fe ....Zero-shot and few-shot learning with deep knowledge transfer. This project aims to develop few-shot and zero-shot learning, visual recognition techniques that can learn a visual concept with few or no visual examples. Visual recognition is a major component in Artificial Intelligence and used in cybernetic security, robotic vision and medical image analysis. This project will use deep learning to enable the zero/few-shot learning to use and model previously unexplored information, making zero/few-shot learning more practical, scalable and flexible. The project is expected to advance the applicability of visual recognition in many challenging scenarios and provide effective tools to analyse the online visual data for supporting Australia’s cybernetic security.Read moreRead less
Simulation and verification of system-level specifications of requirements and constraints using Rosetta. Modern computer-based systems comprise a mixture of electronic hardware and embedded computer software that interacts with mechanical and other non-electrical subsystems. Future design capability will depend on being able to model the requirements and constraints of heterogeneous systems, so that they can be simulated and formally verified before being manufactured and deployed. This project ....Simulation and verification of system-level specifications of requirements and constraints using Rosetta. Modern computer-based systems comprise a mixture of electronic hardware and embedded computer software that interacts with mechanical and other non-electrical subsystems. Future design capability will depend on being able to model the requirements and constraints of heterogeneous systems, so that they can be simulated and formally verified before being manufactured and deployed. This project will develop techniques and software tools for simulation and verification based on the new Rosetta system-level design language. These tools will make the design of complex computer-based systems faster, more reliable and less costly by minimizing design errors early in the design flow.Read moreRead less
Interacting with visualisations of extremely large graph structures on large displays. The latest technological progressions have delivered very large data sets that can be modelled as graphs or networks. Examples include: social networks, biological data, and software structures. This project will develop techniques to allow users to visualise the graphs in the entirety and directly interact with data.
Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those ....Statistical Methods of Model Fitting and Segmentation in Computer Vision. Electronic sensors such as cameras and lasers can provide a rich source of information about the position, shape, and motion of objects around us. However, to extract this information in a reliable, automatic, and accurate way requires a sophisticated statistical theory of the process. Example applications include: video surveillance (better automatic detection of moving people and vehicles and of characterising what those people and vehicles are doing), industrial prototyping and inspection (measuring the size and shape of objects), urban planning (laser scanning streetscapes to create computer models of cities), entertainment industry (movie special effects and games), etc. Read moreRead less
Efficient data mining methods for evidence-based decision making. This project aims to develop efficient data mining methods for causal predictions. Evidence-based decision making (EBD), such as evidence-based medicine and policy, is always preferable. To support EBD, causal predictions forecast how outcomes change when conditions are manipulated. Progress has been made in theoretical research on causal inference based on observational data, but few methods can automatically mine causal signals ....Efficient data mining methods for evidence-based decision making. This project aims to develop efficient data mining methods for causal predictions. Evidence-based decision making (EBD), such as evidence-based medicine and policy, is always preferable. To support EBD, causal predictions forecast how outcomes change when conditions are manipulated. Progress has been made in theoretical research on causal inference based on observational data, but few methods can automatically mine causal signals from the data and methods for efficient causal predictions based on data are even fewer. This project will apply its methods to biomedical problems. The outcomes could support smart and data-driven evidence based decision making in many areas, such as therapeutics and government policy making.Read moreRead less
Early detection of component incompatibility in time-dependent computer architectures. Complex real-time systems are increasingly being built by integrating off-the-shelf components. There are obvious benefits to this approach, but the hidden costs associated with integration are still a major problem. Our proposed approach will enable early detection of integration problems, and thus provide potential for large cost savings. This brings with it clear benefits to industry. One industry that woul ....Early detection of component incompatibility in time-dependent computer architectures. Complex real-time systems are increasingly being built by integrating off-the-shelf components. There are obvious benefits to this approach, but the hidden costs associated with integration are still a major problem. Our proposed approach will enable early detection of integration problems, and thus provide potential for large cost savings. This brings with it clear benefits to industry. One industry that would benefit by such technology is the Australian Navy, which is increasingly being confronted with the challenge of integrating off-the-shelf components in large Naval Combat Systems. Read moreRead less
ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less
Hardware Verification Techniques for Complex High Performance Systems-on-a-chip. Verifying the correctness of modern integrated circuit designs is a critical success factor from both economic and technological perspectives. Rapid advances in semiconductor manufacturing technology are not matched by similar gains in hardware design verification methodology. This creates a widening verification gap that threatens the viability of future complex integrated circuits. This project aims to address th ....Hardware Verification Techniques for Complex High Performance Systems-on-a-chip. Verifying the correctness of modern integrated circuit designs is a critical success factor from both economic and technological perspectives. Rapid advances in semiconductor manufacturing technology are not matched by similar gains in hardware design verification methodology. This creates a widening verification gap that threatens the viability of future complex integrated circuits. This project aims to address this issue by developing novel hardware verification techniques targeting complex high performance systems-on-a-chip. The research outcome will be a set of verification techniques and tools that directly benefit the advancement of future integrated circuit development, verification and manufacturing.Read moreRead less