Deep Learning that Scales. Deep learning has dramatically improved the accuracy of a breathtaking variety of tasks in AI such as image understanding and natural language processing. This project addresses fundamental bottlenecks when attempting to develop deep learning applications at scale. First, this project proposes efficient neural architecture search that is orders of magnitude faster than previously reported, abstracting away the most complex part of deep learning. Second, we will desig ....Deep Learning that Scales. Deep learning has dramatically improved the accuracy of a breathtaking variety of tasks in AI such as image understanding and natural language processing. This project addresses fundamental bottlenecks when attempting to develop deep learning applications at scale. First, this project proposes efficient neural architecture search that is orders of magnitude faster than previously reported, abstracting away the most complex part of deep learning. Second, we will design very efficient binary networks, enabling large-scale deployment of deep learning to mobile devices. Thus this project will overcome two primary limitations of deep learning generally, however, and will greatly increase its already impressive domain of practical application.Read moreRead less
Biological determinants of the safety and stability of neuroprosthetic stimulation electrodes. Performance of cochlear implants and the quality of sound perceived by patients is strongly related to electrode impedance. Electrode impedance fluctuates relative to the implant electrical activity, but the mechanisms which cause this are not clear. This project aims to investigate the role of protein adsorption in electrode performance, including impedance and material dissolution. To enable these in ....Biological determinants of the safety and stability of neuroprosthetic stimulation electrodes. Performance of cochlear implants and the quality of sound perceived by patients is strongly related to electrode impedance. Electrode impedance fluctuates relative to the implant electrical activity, but the mechanisms which cause this are not clear. This project aims to investigate the role of protein adsorption in electrode performance, including impedance and material dissolution. To enable these investigations a new biomimetic analogue of the perilymph (cochlea fluid) is intended to be developed. Additionally, the project aims to investigate two strategies to minimise impedance changes: small pulse electrode cleaning and antifouling coatings. Understanding and control of factors influencing electrode stability aim to facilitate next-generation implant designs.Read moreRead less
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
Targeting electrical stimulation of neural tissue. This project aims to develop a platform of mathematical methods for targeting electrical stimulation of neural tissue. The proposed methods work by selecting the amplitude and polarity of each stimulating electrode in an array based on a desired pattern of neural activation. The algorithms are particularly applicable to high-density electrode arrays. The project will work with an Australian industry leader to provide significant benefits to Aust ....Targeting electrical stimulation of neural tissue. This project aims to develop a platform of mathematical methods for targeting electrical stimulation of neural tissue. The proposed methods work by selecting the amplitude and polarity of each stimulating electrode in an array based on a desired pattern of neural activation. The algorithms are particularly applicable to high-density electrode arrays. The project will work with an Australian industry leader to provide significant benefits to Australia’s high-tech sector through increased knowledge and capacity.Read moreRead less
Feedthrough technologies for polymeric encapsulated active implants. The project will address the scientific challenges of signal transfer between tissue and novel active implantable medical devices, with major implications for cochlear implant manufacture. This will lead to improvements in the quality of life of the hearing-impaired, and will make an important contribution to the development of other sensory implants.
Development of a three dimensional audio-visual next generation speech recognition system. To overcome the disadvantages of current Audio-Visual Speech Recognition Systems, we propose a set of robust algorithms in three dimensional computer vision and speech processing. The proposed system will have far-reaching implications in various areas, for example, human-machine interaction for speech recognition in automated dialog systems and voice-to-text conversions.
Human Cues for Robot Navigation. The world has many navigational cues for the benefit of humans: sign posts, maps and the wealth of information on the internet. Yet, to date, robotic navigation has made little use of this abundant symbolic information as a resource. This project will develop a robot navigation system that can navigate using information beyond the robot's range sensors by incorporating knowledge gained by reading room labels, following human route directions or interpreting maps ....Human Cues for Robot Navigation. The world has many navigational cues for the benefit of humans: sign posts, maps and the wealth of information on the internet. Yet, to date, robotic navigation has made little use of this abundant symbolic information as a resource. This project will develop a robot navigation system that can navigate using information beyond the robot's range sensors by incorporating knowledge gained by reading room labels, following human route directions or interpreting maps found on the web. This project will demonstrate the robot's navigation ability by comparing its performance with a human as it learns to find its way around campus by asking for directions, reading signs and maps, and searching the internet for clues.Read moreRead less
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less
An automatic markerless three-dimensional (3D) motion analysis system for aquatic environments. Australia's sporting performance on the international stage forms an integral part of the psyche of Australians. This project applies latest 3D imaging and biomechanical techniques to quantify swimmers' movement patterns, thereby ensuring Australia's continued elite sporting success and consolidating its current lead in world class technologies.
Computational neural modelling of bottom-up information and top-down attention in auditory perception. The aim of this project is to gain a better understanding of the ways in which our auditory cortex functions. This project will make a significant contribution to this important and fundamental aspect of brain science and brain-inspired computation. The outcome will be to build a computational model of the auditory cortex, through simulation of the detailed neuronal responses using spiking neur ....Computational neural modelling of bottom-up information and top-down attention in auditory perception. The aim of this project is to gain a better understanding of the ways in which our auditory cortex functions. This project will make a significant contribution to this important and fundamental aspect of brain science and brain-inspired computation. The outcome will be to build a computational model of the auditory cortex, through simulation of the detailed neuronal responses using spiking neurons. Applications will develop improved processing strategies for automatic speech recognition, hearing aids, bionic ears (cochlear implants), robotics and other machine processing systems.Read moreRead less