Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve s ....Enhanced Through-Wall Imaging using Bayesian Compressive Sensing. The aim of this project is to develop radar imaging techniques which enable us to 'see' objects behind walls and opaque materials. The major intended breakthrough is the ability to image objects behind walls and inside buildings or enclosed structures without accessing the scene. Novel signal and image processing algorithms, based on Bayesian compressive sensing, will be developed to enhance image quality and resolution, improve speed of operation, and reduce the cost and time of data acquisition and processing. Many applications are expected to benefit from this research including search and rescue, surveillance, security, and defence. The research outcomes are expected to enhance the capabilities of the Australian armed forces, counter-terrorism, police and law-enforcement agencies.Read moreRead less
Joint modelling and recognition of linguistic and paralinguistic speech information. A new modelling framework will be developed exploiting interdependence between linguistic and paralinguistic cues to improve automatic recognition of emotion-related information. Applications in the high-tech industry include automatic routing of angry telephone customers or pre-suicidal crisis centre callers to specialist operators/clinicians.
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic ....Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic noisy speech signals and the ‘cocktail party problem’ using innovative binaural feedback systems. This work should provide significant benefits, including improved voice biometrics and selective auditory attention capabilities in machines.Read moreRead less
Visual Simultaneous Localisation and Mapping in Deformable Environments. This project aims to investigate the problem of building a three-dimensional map of a deformable environment in real-time using images and at the same time localising the camera within the map. This project expects to generate new knowledge in the area of simultaneous localisation and mapping in deformable environments using visual sensors. Expected outcomes include in-depth understanding of the fundamental sensing requirem ....Visual Simultaneous Localisation and Mapping in Deformable Environments. This project aims to investigate the problem of building a three-dimensional map of a deformable environment in real-time using images and at the same time localising the camera within the map. This project expects to generate new knowledge in the area of simultaneous localisation and mapping in deformable environments using visual sensors. Expected outcomes include in-depth understanding of the fundamental sensing requirements for the problem to be solvable, the achievable accuracy, and efficient algorithms for achieving accurate three-dimensional reconstruction of deformable environments. The research outcomes from this project offer significant benefits to diverse areas such as minimally invasive robotic surgery.Read moreRead less
Integrating biologically-inspired auditory models into deep learning. This project aims to discover how a biologically inspired auditory model can be tightly integrated into a state-of-the-art deep learning speech processing framework, to model, design and verify a deep learning based auditory model. Voice-based technologies, ranging from cochlear implants to smart homes, are growing at a rapid pace and speech interfaces are being integrated with all aspects of our lives. However, there is a gro ....Integrating biologically-inspired auditory models into deep learning. This project aims to discover how a biologically inspired auditory model can be tightly integrated into a state-of-the-art deep learning speech processing framework, to model, design and verify a deep learning based auditory model. Voice-based technologies, ranging from cochlear implants to smart homes, are growing at a rapid pace and speech interfaces are being integrated with all aspects of our lives. However, there is a growing demand to improve these voice-enabled services, making them more secure and less open to cyber-crime attack by unauthorised users. The project is expected to improve techniques for modelling and automatic processing of speech and audio signals, which should provide significant benefits, including improved voice biometrics and cochlear implants.Read moreRead less
Drone-based Communications for High-speed Beyond 5G Wireless Systems. Drone-based communication is a revolutionised wireless paradigm for the development of highly flexible and cost-effective beyond fifth-generation (B5G) wireless systems. This project aims to develop novel communication theories and practical techniques to realise truly high-speed and ubiquitous communication required in B5G networks. The project intends to deliver resource allocation designs, robust transceiver designs and a s ....Drone-based Communications for High-speed Beyond 5G Wireless Systems. Drone-based communication is a revolutionised wireless paradigm for the development of highly flexible and cost-effective beyond fifth-generation (B5G) wireless systems. This project aims to develop novel communication theories and practical techniques to realise truly high-speed and ubiquitous communication required in B5G networks. The project intends to deliver resource allocation designs, robust transceiver designs and a system-level analysis as the foundations and tools to unlock the potential of this promising paradigm. The outcomes of this project are expected to fundamentally advance the knowledge of drone-based communications with significant economic values to service providers and benefits to mobile users over the world.Read moreRead less
Robotic Perception with Unconventional Sensors . Autonomy in robotic systems currently relies on conventional sensors such as lasers and cameras. Alternative sensing modalities as in the case of active electromagnetic sensors are commonly used to detect flaws, cracks and assess infrastructure’s integrity, however, fundamental research questions preclude their use for robotic perception. This project will develop the theory and algorithms to enable perception tasks such as localisation, mapping a ....Robotic Perception with Unconventional Sensors . Autonomy in robotic systems currently relies on conventional sensors such as lasers and cameras. Alternative sensing modalities as in the case of active electromagnetic sensors are commonly used to detect flaws, cracks and assess infrastructure’s integrity, however, fundamental research questions preclude their use for robotic perception. This project will develop the theory and algorithms to enable perception tasks such as localisation, mapping and recognition with unconventional sensors. The outcomes of this research have the potential to improve the effectiveness of critical civil infrastructure maintenance technology through accurate and reliable inspections, and the reduced need for human intervention.Read moreRead less
Development of globally optimal solutions to simultaneous localisation and mapping for robot navigation. Building robots that can operate on their own is one of the potentially transformational technologies of this century. This project will develop algorithms that are well understood and robust to allow the deployment of robots in environments populated with people and in search and rescue operations where global positioning system is not available.
Discovery Early Career Researcher Award - Grant ID: DE140100420
Funder
Australian Research Council
Funding Amount
$394,704.00
Summary
Large Scale Multiple Antennas for Energy-Efficient Heterogeneous Wireless Networks. This project investigates new network architectures for future wireless broadband inspired by recent advances in large scale multiple antenna technology and heterogeneous networks. The aim is to support flexible and scalable wireless services across diverse network regions with energy-efficient management of radio spectrum and interference. Targeted applications include smart energy metering, intelligent transpor ....Large Scale Multiple Antennas for Energy-Efficient Heterogeneous Wireless Networks. This project investigates new network architectures for future wireless broadband inspired by recent advances in large scale multiple antenna technology and heterogeneous networks. The aim is to support flexible and scalable wireless services across diverse network regions with energy-efficient management of radio spectrum and interference. Targeted applications include smart energy metering, intelligent transport systems, mobile health monitoring and green data centres. Outcomes of the research will be new wireless protocols and algorithms drawing upon the foundations of random matrix theory, game theory and large system analysis, which will offer fundamental insights into large scale multiple antennas for heterogeneous wireless networks.Read moreRead less