Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less
Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with thei ....Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with their environment, and the simulation of spatiotemporal deformations in anatomical organs. Benefits include a better understanding of growth processes, predictive models of how degenerative diseases progress and a computational framework that will assist in designing proper mitigation and intervention strategies.Read moreRead less
Tensor and Hypergraph Methods in Fitting Visual Data. This proposal will put an important class of clustering (extracting data that should fit a geometric model) on a more solid theoretical foundation. This will lead to better understanding of how to certify outcomes, efficiency, reliability etc. The type of clustering under consideration is relevant to many problems in machine learning and computer vision, as well as data mining and a wide variety of other settings.
Passive Positioning and Tracking of Flying Objects Using Satellite Signals. Along with the deployment of low Earth orbit satellite constellations for global satellite Internet services, such as Starlink, Ku/Ka/V band microwave signals from space will be available anywhere on Earth 24/7. Utilising the microwave signals, this project aims to investigate a high-resolution cost-effective solution to position and track un-cooperative flying objects, and expects to generate new knowledge in the area o ....Passive Positioning and Tracking of Flying Objects Using Satellite Signals. Along with the deployment of low Earth orbit satellite constellations for global satellite Internet services, such as Starlink, Ku/Ka/V band microwave signals from space will be available anywhere on Earth 24/7. Utilising the microwave signals, this project aims to investigate a high-resolution cost-effective solution to position and track un-cooperative flying objects, and expects to generate new knowledge in the area of remote sensing and to make Australia the leader in passive flying objects positioning and tracking. This should provide significant benefits, such as enabling new applications for future drone delivery systems or aerial taxi services, and benefiting the air transport industry, the defence industry, and bird conservation.Read moreRead less
Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learni ....Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learning architectures that are inherently robust. The outcomes of this project will increase the security and reliability of computer vision by detecting, reporting and nullifying such attacks and will benefit the general public and industry on many fronts.Read moreRead less
Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord ....Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.Read moreRead less
3D tomographic reconstruction of rainfall using satellite signals. This project aims to use the microwave communication links of low earth and/or medium earth orbit satellites to achieve three dimensional tomographic reconstruction of rainfall. The path loss of microwave signals due to rainfall, known as rain attenuation can be used to measure rain. Similar to using X-ray to carry out human-body CT scans. With the aid of advanced signal processing techniques, the proposed method will achieve 3D ....3D tomographic reconstruction of rainfall using satellite signals. This project aims to use the microwave communication links of low earth and/or medium earth orbit satellites to achieve three dimensional tomographic reconstruction of rainfall. The path loss of microwave signals due to rainfall, known as rain attenuation can be used to measure rain. Similar to using X-ray to carry out human-body CT scans. With the aid of advanced signal processing techniques, the proposed method will achieve 3D measurements with resolution and coverage unachievable before, paving the way for innovative water relevant applications such as hydrology and agriculture, and new findings in atmospheric research.Read moreRead less
Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor ....Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor authentication performance, which is not commercially applicable. This project aims to investigate innovative solutions to this issue. The intended deliverables will include deep learning based biometric feature extractor, cancellable biometrics and cloud oriented biometrics security protocols. Read moreRead less
Understanding political debate and policy decisions using big data. This project aims to empirically test a novel framework for analysing the relationship between political debates and policy decisions. Using digital sources and computational modelling approaches, it will investigate three specific issues to test this framework. These issues, all drawn from different policy sectors, will be examined as a series of debates linked to specific decisions, over the last two decades. The expected outc ....Understanding political debate and policy decisions using big data. This project aims to empirically test a novel framework for analysing the relationship between political debates and policy decisions. Using digital sources and computational modelling approaches, it will investigate three specific issues to test this framework. These issues, all drawn from different policy sectors, will be examined as a series of debates linked to specific decisions, over the last two decades. The expected outcomes will provide insights into links between political debates and policy decisions with potential benefits for politics and policy-making.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