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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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
Learning to see in 3D. The project aims to endow machine vision with an ability we, as humans, use almost constantly: to judge 3D properties from a 2D image. This extremely useful ability will be applied to digital images to obtain 3D measurements and aid in automating tasks such as mining, surveying, medical diagnosis, and visual effects in movies.
Recognising and reconstructing objects in real time from a moving camera. This project will use a moving camera to estimate the three-dimensional shape and identity of objects and surfaces it can see. This ability, which we humans use all the time, has wide application in automation including driver assistance, exploring hazardous environments, robotics, remote collaboration, and the creation of three-dimensional models for entertainment.
Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result giv ....Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result given the input data in a short amount of time. The expected outcomes would support the construction of reliable and accurate computer vision-based systems, such as large-scale 3-D reconstruction from photo collections, self-driving cars and domestic robots.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL130100102
Funder
Australian Research Council
Funding Amount
$3,179,946.00
Summary
Lifelong computer vision systems. This project will create a computer vision system that can produce a detailed environmental map in real time, turning standard video cameras into sensors that 'understand' a scene with basic semantic tools. This high-level sensing will unlock a wide range of applications for autonomous systems.
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
Model-based error location in Java programs. The construction of modern software requires extensive testing and
debugging in addition to using appropriate specification, design, and
verification techniques. Testing and debugging are very time-consuming
and costly, drawing - according to recent articles - "typically 50%
or more of the resources for software projects''. By providing a new,
flexible approach to the debugging of complex software, this project
offers the potential of significant cost ....Model-based error location in Java programs. The construction of modern software requires extensive testing and
debugging in addition to using appropriate specification, design, and
verification techniques. Testing and debugging are very time-consuming
and costly, drawing - according to recent articles - "typically 50%
or more of the resources for software projects''. By providing a new,
flexible approach to the debugging of complex software, this project
offers the potential of significant cost savings, highly beneficial to
the ICT industry. Lessons learned from the demonstration prototype,
can be directly carried over into commercial tool development. In
addition, the project strengthens links to high quality European
research laboratories.Read moreRead less
Model-based error location in concurrent software. The construction of modern software requires extensive testing and debugging in addition to using appropriate specification, design, and verification techniques. Testing and debugging are very time-consuming and costly, drawing - according to recent articles - ``typically 50\% or more of the resources for software projects''. By extending the power of a new, flexible debugging approach, this project offers the potential of significant cost savin ....Model-based error location in concurrent software. The construction of modern software requires extensive testing and debugging in addition to using appropriate specification, design, and verification techniques. Testing and debugging are very time-consuming and costly, drawing - according to recent articles - ``typically 50\% or more of the resources for software projects''. By extending the power of a new, flexible debugging approach, this project offers the potential of significant cost savings, highly beneficial to any industry with a significant ICT component, e.g., defense. Lessons learned from the demonstration prototype, can be directly carried over into commercial tool development. The project strengthens links to high quality European research laboratories.Read moreRead less