Design of Multi-Gigabit Millimeter Wave Cellular Networks. It has been predicted that within the next ten years trillions of devices will connect to cellular networks and cause a thousand-fold increase in mobile traffic. This will lead to a severe spectrum shortage and congested cellular networks. Large expanses of the millimetre-wave spectrum have the potential to meet the capacity demands of future cellular networks. The project aims to develop the fundamental sciences for millimetre-wave cell ....Design of Multi-Gigabit Millimeter Wave Cellular Networks. It has been predicted that within the next ten years trillions of devices will connect to cellular networks and cause a thousand-fold increase in mobile traffic. This will lead to a severe spectrum shortage and congested cellular networks. Large expanses of the millimetre-wave spectrum have the potential to meet the capacity demands of future cellular networks. The project aims to develop the fundamental sciences for millimetre-wave cellular communications, which thought to be essential for the design of next generation cellular networks with data rates at least three orders of magnitude faster than those in current cellular networks. The research outcomes are expected to provide the foundations and tools for building a future mobile broadband network infrastructure in Australia.Read moreRead less
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less
Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vecto ....Semantic Vectorisation: From Bitmaps to Intelligent Representations. The objective of this innovative project is to provide a solution to the open question of representing natural images by semantically rich vector graphics. The challenges are to identify key visual and temporal elements for images and videos, and efficiently decompose the visual data into semantic vector representations that are faithful to original data, compact and editable. The project aims to investigate new bitmap-to-vector conversion methods. It is expected to develop a framework where semantic labels and hyperlinks can be embedded in visual data automatically. It hopes to pioneer the creation of a web of images where the links are on image/video regions. New image simplification, stylisation, and non-photorealistic rendering methods are expected to be provided.Read moreRead less
Sampling and processing for diffusion magnetic resonance imaging. This project aims to develop optimal, efficient and robust signal processing methods for diffusion magnetic resonance imaging (dMRI) with reduced scan times. A child, possibly distressed, can only be motionless long enough to undergo a basic dMRI scan of the brain, but enhanced forms of dMRI need at least 60 minutes. The project’s processing methods will use spherical geometries, which encode information about white matter fibres ....Sampling and processing for diffusion magnetic resonance imaging. This project aims to develop optimal, efficient and robust signal processing methods for diffusion magnetic resonance imaging (dMRI) with reduced scan times. A child, possibly distressed, can only be motionless long enough to undergo a basic dMRI scan of the brain, but enhanced forms of dMRI need at least 60 minutes. The project’s processing methods will use spherical geometries, which encode information about white matter fibres in the brain, to collect and reconstruct images. The project is expected to reduce dMRI scan times and ultimately make non-invasive and inexpensive early detection of neurological disorders such as dementia feasible.Read moreRead less
Enabling ultra-reliable and sustainable machine-to-machine communications. This project aims to develop spectrum sharing and power transfer techniques for machine-to-machine communications in future wireless networks. Current wireless networks have high data rate as a priority but cannot deliver ultra-reliable and extended battery life operation for many low data rate machine-type devices. Through proper design of wireless and autonomous machine-to-machine communications, this project expects to ....Enabling ultra-reliable and sustainable machine-to-machine communications. This project aims to develop spectrum sharing and power transfer techniques for machine-to-machine communications in future wireless networks. Current wireless networks have high data rate as a priority but cannot deliver ultra-reliable and extended battery life operation for many low data rate machine-type devices. Through proper design of wireless and autonomous machine-to-machine communications, this project expects to improve quality of life and implement ultra-reliable, intelligent and long lasting machine-type monitoring devices for health, agriculture, mining, wildlife and critical national infrastructure.Read moreRead less
Reconceiving Machine Learning. The proposed research will develop a new way to consider problems to which machine learning can be applied. Machine learning is crucial enabler of the digital economy. The research will provide better opportunities for Australian industry to gain a competitive advantage with machine learning technology. The framework developed will enable better opportunities for collaborative research and will build and strengthen international linkages.
Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected ....Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected outcomes include the
development of software that allows the solution of hitherto unsolved machine
learning problems, and the ability to solve problems larger than those solvable
by the current generation of machine learning tools.Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less
Artificial intelligence meets wireless sensor networks: filling the gaps between sensors using spatial reasoning. Monitoring potential disaster regions and integrating available information with expert knowledge can prevent disasters and save many lives. The outcome of our project is one of the key components for intelligent systems that can autonomously monitor the environment, make the correct inferences and issue appropriate warnings and recommendations.
Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global com ....Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global competitiveness. Expected outcomes of this project will help to break the communication barriers between the Deaf and hearing population. This should provide significant benefits to Deaf communities through enhanced communication and improved quality-of-life, leading to a fair, more inclusive and resilient Australian society.Read moreRead less