Deep Learning Architecture with Context Adaptive Features for Image Parsing. This project aims to develop a novel deep learning network architecture with contextual adaptive features for image parsing that can improve the object detection accuracy in real-world applications. A number of innovative methods for deep learning, contextual features and network parameter selection will be developed and investigated. The impact of the proposed architecture and features will be improved object-detection ....Deep Learning Architecture with Context Adaptive Features for Image Parsing. This project aims to develop a novel deep learning network architecture with contextual adaptive features for image parsing that can improve the object detection accuracy in real-world applications. A number of innovative methods for deep learning, contextual features and network parameter selection will be developed and investigated. The impact of the proposed architecture and features will be improved object-detection accuracy and advances in deep learning network architecture for image parsing. The intended outcomes are deep learning network architecture, contextual feature extraction techniques and network parameter optimisation techniques for image parsing.Read moreRead less
A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less
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
Australian Laureate Fellowships - Grant ID: FL210100045
Funder
Australian Research Council
Funding Amount
$3,245,263.00
Summary
Energy-efficient artificial intelligence using quantum technologies. Artificial intelligence (AI) is transforming society but standard technologies come with significant hidden costs: training even a single, common, learning model can emit 5 times more carbon dioxide than the lifetime emissions of the average car. This Fellowship aims to develop artificial intelligence platforms using Australia’s significant investment in quantum technologies to bypass traditional approaches to AI. The expected ....Energy-efficient artificial intelligence using quantum technologies. Artificial intelligence (AI) is transforming society but standard technologies come with significant hidden costs: training even a single, common, learning model can emit 5 times more carbon dioxide than the lifetime emissions of the average car. This Fellowship aims to develop artificial intelligence platforms using Australia’s significant investment in quantum technologies to bypass traditional approaches to AI. The expected outcomes are neuromorphic computers that operate efficiently—with low-energy cost—and rapidly—achieving speeds impossible with conventional electronic approaches. The anticipated benefits are transformative technologies for AI, new applications across society, and new tools for exploring brain function and cognition.Read moreRead less
A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst provid ....A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst providing valuable training/education for the community stakeholders involved in the production of the system. The research outcome will be globally significant, enabling end users to meet key water quality objectives over time, and considerably increase productivity in the Australian agriculture/aquaculture industries.Read moreRead less
Recombination and the genomic landscape of speciation. This project aims to evaluate how genomes become different during the origin of species by utilising an innovative system where multiple replicates of the speciation process exist. This project expects to generate knowledge in the area of speciation genetics by exploring the effects of sex, migration and selection on the diversity of hundreds of genomes from an Australian wildflower. Expected outcomes of this project include a deeper underst ....Recombination and the genomic landscape of speciation. This project aims to evaluate how genomes become different during the origin of species by utilising an innovative system where multiple replicates of the speciation process exist. This project expects to generate knowledge in the area of speciation genetics by exploring the effects of sex, migration and selection on the diversity of hundreds of genomes from an Australian wildflower. Expected outcomes of this project include a deeper understanding of the maintenance of genetic diversity in natural populations, and development of a model organism for studying the genetics and ecology of speciation. This project should provide significant benefits including enhanced capacity in evolutionary genetics in Australia.Read moreRead less
A Space-Based Quantum Communications Platform using Continuous Variables. This work proposes to investigate a new space-borne platform capable of quantum communications with a terrestrial ground station. Different from existing space-borne quantum communication platforms, our new platform will be based on CV (Continuous Variable) technology and will integrate the ability to seamlessly switch to classical Free-Space Optical communications when channel conditions deem quantum communications are .... A Space-Based Quantum Communications Platform using Continuous Variables. This work proposes to investigate a new space-borne platform capable of quantum communications with a terrestrial ground station. Different from existing space-borne quantum communication platforms, our new platform will be based on CV (Continuous Variable) technology and will integrate the ability to seamlessly switch to classical Free-Space Optical communications when channel conditions deem quantum communications are too difficult. Currently no quantum satellite built on CV technology exists. Our research will produce a significant advance in an emerging technology space, and will allow Australia to take scientific leadership in an important aspect of ultra-secure communications from satellites.
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Evolutionary models and biodiscovery tools from neurotoxic snake venoms. This project aims to identify the selection pressures that shape snake venom neurotoxins and how they interact with nicotinic acetylcholine receptors, and to elucidate their biodiscovery potential. This project aims to test these important toxins on model systems that represent natural prey items in order to determine the molecular and functional evolution of neurotoxic peptides. Expected outcomes include substantial contri ....Evolutionary models and biodiscovery tools from neurotoxic snake venoms. This project aims to identify the selection pressures that shape snake venom neurotoxins and how they interact with nicotinic acetylcholine receptors, and to elucidate their biodiscovery potential. This project aims to test these important toxins on model systems that represent natural prey items in order to determine the molecular and functional evolution of neurotoxic peptides. Expected outcomes include substantial contributions to the body of evolutionary biology knowledge, while also having the applied benefit of discovering novel compounds with potential for use in drug design and discovery. These outcomes will benefit Australian science and society by elucidating fundamental processes while revealing biodisovery resources.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100477
Funder
Australian Research Council
Funding Amount
$421,554.00
Summary
Advancing Human Perception: Countering Evolving Malicious Fake Visual Data. The aim of this project is to provide new effective and generalisable deepfake detection methods for automatically detecting maliciously manipulated visual data generated by misused artificial intelligence (AI) techniques. It will present innovative computer vision and image processing knowledge and techniques, enabling the developed methods to advance human perception in recognising fake data, enhance cybersecurity, and ....Advancing Human Perception: Countering Evolving Malicious Fake Visual Data. The aim of this project is to provide new effective and generalisable deepfake detection methods for automatically detecting maliciously manipulated visual data generated by misused artificial intelligence (AI) techniques. It will present innovative computer vision and image processing knowledge and techniques, enabling the developed methods to advance human perception in recognising fake data, enhance cybersecurity, and protect privacy in AI applications. The anticipated outcomes should provide significant benefits to a wide range of applications, such as providing timely alerts to the media, government organisations, and the industry about misleading fake visual data, and preventing financial crimes on synthetic identity fraud.Read moreRead less
Predicting genetic exchange between species under climate change. This project aims to resolve the factors that lead to the mixing of species’ gene pools, with a focus on whether climate change will increase such mixing, possibly leading to extinction by genetic swamping.
The significance is that the project would improve our understanding of speciation and species’ vulnerability to rapid climate change through genetic mixing; a largely overlooked process.
Key outcomes would be to generate new k ....Predicting genetic exchange between species under climate change. This project aims to resolve the factors that lead to the mixing of species’ gene pools, with a focus on whether climate change will increase such mixing, possibly leading to extinction by genetic swamping.
The significance is that the project would improve our understanding of speciation and species’ vulnerability to rapid climate change through genetic mixing; a largely overlooked process.
Key outcomes would be to generate new knowledge of a fundamental evolutionary process and extend the toolbox of biodiversity managers facing rapid environmental change.
The project would benefit Australia by highlighting our unique biodiversity and scientific capability, and by training early career researchers in advanced evolutionary biology.Read moreRead less