Enhanced ultrasound-based imaging using image-based registration and acoustic impedance reconstruction. The project will nurture the development of a new centre for medical image analysis work in Australia at the ANU. This is in line with the vision of ANU's Department of Engineering for the growth of biomedical engineering research. The project is directed at the creation of new surgical and imaging techniques based on ultrasound. These will have a direct effect on improved healthcare and new c ....Enhanced ultrasound-based imaging using image-based registration and acoustic impedance reconstruction. The project will nurture the development of a new centre for medical image analysis work in Australia at the ANU. This is in line with the vision of ANU's Department of Engineering for the growth of biomedical engineering research. The project is directed at the creation of new surgical and imaging techniques based on ultrasound. These will have a direct effect on improved healthcare and new clinical procedures. The creation of a new ultrasound imaging modality will have commercial applications, enhancing the growth of biomedical engineering in Australia. The training of new PhD students and postdoctoral fellows will provide a basis for further development in this area, and its extension to other imaging research in Australia. Read moreRead less
Computer vision from a multi-structural analysis framework. Computer vision has applications in a wide variety of areas: security (video surveillance), entertainment (special effects), health care (medical imaging), and economy (improved automation and consumer products). This project will improve the accuracy and reliability of such applications. Advances will also lead to new products and industries.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0775672
Funder
Australian Research Council
Funding Amount
$150,000.00
Summary
3D Scanning and Printing Facilities (3DSPF). A one-stop shop is proposed to accommodate 3D scanning and printing facilities in WA to advance a range of research projects currently undertaken by internationally renowned researchers in their respective fields. The facility will impact on our research programs in a wide range of disciplines including rapid prototyping, robotics, geomatics, demining, nanotechnology, and molecular modeling. These projects are of high significance and will advance res ....3D Scanning and Printing Facilities (3DSPF). A one-stop shop is proposed to accommodate 3D scanning and printing facilities in WA to advance a range of research projects currently undertaken by internationally renowned researchers in their respective fields. The facility will impact on our research programs in a wide range of disciplines including rapid prototyping, robotics, geomatics, demining, nanotechnology, and molecular modeling. These projects are of high significance and will advance research in most of the national priorities. The facility can also be used for training and teaching purposes. The facility builds on a previous long range scanning facility and on the State Government's support of leading edge computational and visualization facilities. Read moreRead less
Intelligent Virtual Human Companions. This research aims to develop intelligent virtual human companions that can seemingly integrate our immediate physical environment and understand their surroundings including people’s emotions, behaviours, actions and interactions. Such a technology will be enabled by leveraging recent advances in mixed/augmented reality technologies, and by developing innovative artificial intelligence and computer vision and graphics algorithms for dynamic real-world envir ....Intelligent Virtual Human Companions. This research aims to develop intelligent virtual human companions that can seemingly integrate our immediate physical environment and understand their surroundings including people’s emotions, behaviours, actions and interactions. Such a technology will be enabled by leveraging recent advances in mixed/augmented reality technologies, and by developing innovative artificial intelligence and computer vision and graphics algorithms for dynamic real-world environments. Unlike robots, the proposed technology will be low cost, readily deployable and customisable, and will not have any physical limitations or maintenance requirements. It will thus have a wide range of applications from elderly care, healthcare care to educational training.Read moreRead less
Active multispectral computer vision for defence and security. This project will develop new techniques to extract intelligent information from multispectral images in the visible and near infra-red spectrum. It will enable computers to automatically recognise objects, faces and human actions with unprecedented accuracy.
Person identification from multiple non-invasive iris and face biometrics in video. This project will undertake research to develop a prototype system for personal identification that can be used by law enforcement and security agencies to enrol people at points of entry at public places. The system will non-invasively acquire face and iris biometrics and match them against a database of known persons. The proposed system can be used in sensitive buildings for access control, eliminating the nee ....Person identification from multiple non-invasive iris and face biometrics in video. This project will undertake research to develop a prototype system for personal identification that can be used by law enforcement and security agencies to enrol people at points of entry at public places. The system will non-invasively acquire face and iris biometrics and match them against a database of known persons. The proposed system can be used in sensitive buildings for access control, eliminating the need to carry access cards or remember passwords. This research contributes to the national research priority of Safeguarding Australia. We will develop new techniques in computer vision and train new researchers in this area.Read moreRead less
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
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
Application of manifold-based image analysis to identify subtle changes in digitally-captured pathology samples. This project will research and develop advanced computer aided analytics for digital pathology with the aim of automating several common pathology tests. This project should not only greatly increase the speed of pathology tests but should also improve quality, lower costs and improve patient outcomes.