Creating new methods to study structure vision. The majority of the structure within natural images is due to third to fifth order correlations between image points. Research has shown that sensitivity to this higher order structure, provides so called Structure Vision. Research has also shown that as few as three to four brain mechanisms are involved, and these may be related to the Minkowski functionals, which in turn are related to the structural and surface properties of real materials. This ....Creating new methods to study structure vision. The majority of the structure within natural images is due to third to fifth order correlations between image points. Research has shown that sensitivity to this higher order structure, provides so called Structure Vision. Research has also shown that as few as three to four brain mechanisms are involved, and these may be related to the Minkowski functionals, which in turn are related to the structural and surface properties of real materials. This project aims to build on recent discoveries of new stimuli to implement objective tests with which to study structure vision with the Partner Organisation. The project aims to also expand on realistic models of how Structure Vision may be computed by just a few coupled cortical pyramidal cells.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
Discovery Early Career Researcher Award - Grant ID: DE170100128
Funder
Australian Research Council
Funding Amount
$395,000.00
Summary
Information processing in the brain. This project aims to understand the brain's functional organisation by developing non-invasive methods to characterise connectivity between interacting brain regions. No model-based methods to compute directional coupling between brain regions can be applied to large scale networks for resting state functional MRI data. This capability would be a major breakthrough in neuroimaging, given uninformative (non-directional) network connectivity analysis restricts ....Information processing in the brain. This project aims to understand the brain's functional organisation by developing non-invasive methods to characterise connectivity between interacting brain regions. No model-based methods to compute directional coupling between brain regions can be applied to large scale networks for resting state functional MRI data. This capability would be a major breakthrough in neuroimaging, given uninformative (non-directional) network connectivity analysis restricts research. This project is expected to advance our understanding of information processing in the brain by providing a mechanistic approach to functional integration.Read moreRead less
Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelli ....Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelligence to infer and predict dangerous driver and passenger behaviour. This has the potential to significantly benefit society by advancing autonomous driving capabilities and reducing driver-induced accidents and fatalities, ensuring that every driver, passenger and pedestrian arrives home safely at the end of each day.Read moreRead less
ARC Centre of Excellence for Integrative Brain Function. The Centre of Excellence for Integrative Brain Function will address one of the greatest scientific challenges of the 21st century to understand how the brain works. We will investigate complex functions such as attention, prediction and decision-making, which require the coordination of information processing by many areas of the brain. This will require a highly collaborative approach involving neurobiologists, cognitive scientists, eng ....ARC Centre of Excellence for Integrative Brain Function. The Centre of Excellence for Integrative Brain Function will address one of the greatest scientific challenges of the 21st century to understand how the brain works. We will investigate complex functions such as attention, prediction and decision-making, which require the coordination of information processing by many areas of the brain. This will require a highly collaborative approach involving neurobiologists, cognitive scientists, engineers and physicists, allowing us to translate our discoveries into novel technologies for the social and economic benefit of all Australians. We will also train a new generation of multidisciplinary researchers, and contribute our expertise to a range of public education and awareness programs.Read moreRead less
Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results ....Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results will test the generality of principles that have been developed in studies of female mate choice and extend these ideas to address intra-sexual selection operating through opponent assessment.Read moreRead less
Handling unreliable, uncertain and inadequate data for Intelligence led Investigation. Intelligence led investigation has been successful recently in drug and people smuggling, preparation or instigation of acts of terrorism, and can benefit profoundly from the techniques we will develop, in the timely management and inference from many sources and kinds of uncertain information. This work will assist in making Australia a safer and more secure country.
E.g., Australian Bureau of Statistics ....Handling unreliable, uncertain and inadequate data for Intelligence led Investigation. Intelligence led investigation has been successful recently in drug and people smuggling, preparation or instigation of acts of terrorism, and can benefit profoundly from the techniques we will develop, in the timely management and inference from many sources and kinds of uncertain information. This work will assist in making Australia a safer and more secure country.
E.g., Australian Bureau of Statistics figures show that for 2004, investigations of some 35% of murders, 63% of kidnappings, and 80% of robberies are incomplete at 30 days. Terrorism investigations are harder in that usually there is no initial crime trigger for an investigation. Any assistance our tools can provide in will be of significant benefit to Australia.Read moreRead less
Data Adaptive Geophysical Inversion. The goal of this project is to develop new techniques for extracting information about the interior structure of the Earth from large geophysical data sets. These methods will be adaptive so that they allow the definition of the physical model to be constrained by the character of the data. The project will utilize advances in computational geometry, nonlinear inversion and interactive computer visualisation to extract robust information from data sets with v ....Data Adaptive Geophysical Inversion. The goal of this project is to develop new techniques for extracting information about the interior structure of the Earth from large geophysical data sets. These methods will be adaptive so that they allow the definition of the physical model to be constrained by the character of the data. The project will utilize advances in computational geometry, nonlinear inversion and interactive computer visualisation to extract robust information from data sets with variable resolving power. The resulting algorithms will be applicable to a wide range of problems in the physical sciences.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
Discovery Early Career Researcher Award - Grant ID: DE240101129
Funder
Australian Research Council
Funding Amount
$442,000.00
Summary
Synergy between future 21-cm experiments and physical cosmology. The nature of dark matter and formation of the first galaxies are both unsolved mysteries. During the first 500 million years, our universe was filled with hydrogen atoms illuminated by the first galaxies. The 21-cm radiation from this gas encodes properties of unseen galaxies and dark matter during this so-called cosmic dawn. This project aims to build an innovative framework to leverage future 21-cm experiments using The Square K ....Synergy between future 21-cm experiments and physical cosmology. The nature of dark matter and formation of the first galaxies are both unsolved mysteries. During the first 500 million years, our universe was filled with hydrogen atoms illuminated by the first galaxies. The 21-cm radiation from this gas encodes properties of unseen galaxies and dark matter during this so-called cosmic dawn. This project aims to build an innovative framework to leverage future 21-cm experiments using The Square Kilometre Array to observe cosmic dawn, and to forecast the optimal constraints on dark matter physics. Additional outcomes include the largest cosmological simulation of the first galaxies powered by neural networks and improved knowledge of their properties using Bayes' theorem and The James Webb Space Telescope.Read moreRead less