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Australian State/Territory : QLD
Research Topic : Neural coding
Status : Active
Scheme : Discovery Projects
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  • Researchers (29)
  • Funded Activities (8)
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP200102252

    Funder
    Australian Research Council
    Funding Amount
    $480,000.00
    Summary
    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.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210100640

    Funder
    Australian Research Council
    Funding Amount
    $425,912.00
    Summary
    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.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210103430

    Funder
    Australian Research Council
    Funding Amount
    $240,193.00
    Summary
    Attention vs Perception: When is selection optimal, when relational? This project aims to investigate an important, newly discovered dissociation between early visual selection and perceptual decision-making. Contrary to current theories, attentional and perceptual processes are tuned to different stimulus attributes described in the relational vs. optimal account, which implies that current theories of attention do not describe early attention but later, decisional processes. This project will .... Attention vs Perception: When is selection optimal, when relational? This project aims to investigate an important, newly discovered dissociation between early visual selection and perceptual decision-making. Contrary to current theories, attentional and perceptual processes are tuned to different stimulus attributes described in the relational vs. optimal account, which implies that current theories of attention do not describe early attention but later, decisional processes. This project will provide an accurate description of these processes, which promises important theoretical breakthroughs. Work on this project will also significantly advance methods to detect and describe early attentional processes, by identifying error-prone methods of Psychophysics and Neuroscience studies, and proposing remedies.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220103941

    Funder
    Australian Research Council
    Funding Amount
    $608,892.00
    Summary
    Fundamental neurocognitive mechanisms underpinning creative thought. The project aims to understand the neural and cognitive bases of creative thought by using a novel approach and recent framework that has emerged from the study of semantic cognition and executive control functions. Creative thought is fundamental to human advances throughout history and it is the foundation to all arts and sciences. Expected outcomes are a framework that can explain the source of knowledge and the evaluative .... Fundamental neurocognitive mechanisms underpinning creative thought. The project aims to understand the neural and cognitive bases of creative thought by using a novel approach and recent framework that has emerged from the study of semantic cognition and executive control functions. Creative thought is fundamental to human advances throughout history and it is the foundation to all arts and sciences. Expected outcomes are a framework that can explain the source of knowledge and the evaluative mechanisms needed to generate new and useful ideas. Significant benefits will be to advance our understanding of the neurocognitive mechanisms of creative thought, which can enhance Australia’s scientific capability through training and collaboration and broader society by enhancing capacity for innovative thinking.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220100800

    Funder
    Australian Research Council
    Funding Amount
    $350,000.00
    Summary
    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.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190103600

    Funder
    Australian Research Council
    Funding Amount
    $443,000.00
    Summary
    Investigating differences in decision-making ability in older adults. This project aims to investigate how healthy ageing impacts decision making and its associated neural circuits using computation modelling and neurogenetic methods. Decision-making is a fundamental cognitive ability, allowing us to choose the best course of action. This project will investigate the relationship between genes and decision-making performance across the adult lifespan. Expected outcomes include a deeper understan .... Investigating differences in decision-making ability in older adults. This project aims to investigate how healthy ageing impacts decision making and its associated neural circuits using computation modelling and neurogenetic methods. Decision-making is a fundamental cognitive ability, allowing us to choose the best course of action. This project will investigate the relationship between genes and decision-making performance across the adult lifespan. Expected outcomes include a deeper understanding of how decision-making evolves in healthy ageing, and a tool based on genetic scores and computational modelling to predict an individual's trajectory of cognitive function. This could help identify individuals who are at risk for cognitive decline, which could then inform better interventions.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200100127

    Funder
    Australian Research Council
    Funding Amount
    $526,690.00
    Summary
    How the brain produces speech: Neuronal oscillations to neuromodulation. Speech is crucial for facilitating human communication through language, yet there is a lack of clarity about where, when and what type of activity occurs in the brain during key stages of production. This project will use intracranial recordings to characterise neuronal oscillations in combination with direct electrical stimulation, functional neuroimaging and non-invasive brain stimulation to establish critical areas and .... How the brain produces speech: Neuronal oscillations to neuromodulation. Speech is crucial for facilitating human communication through language, yet there is a lack of clarity about where, when and what type of activity occurs in the brain during key stages of production. This project will use intracranial recordings to characterise neuronal oscillations in combination with direct electrical stimulation, functional neuroimaging and non-invasive brain stimulation to establish critical areas and their timecourses with millisecond resolution. The outcome will be a better theoretical account of the brain mechanisms involved in spoken production. The benefit of this new theoretical account will be a better basis for prevention of post-surgical language impairment and neuromodulatory treatments after brain injury.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220101853

    Funder
    Australian Research Council
    Funding Amount
    $448,610.00
    Summary
    A more sound approach to the neurobiology of language. How does the brain attain spoken language? Current neurobiological models assume either implicitly or explicitly that there is no relationship between a word's sound and its meaning. Yet considerable evidence shows this strong assumption about the arbitrariness of language is invalid. This project will use a combination of behavioural, neuroimaging and computational studies to characterise how the brain processes statistical regularities in .... A more sound approach to the neurobiology of language. How does the brain attain spoken language? Current neurobiological models assume either implicitly or explicitly that there is no relationship between a word's sound and its meaning. Yet considerable evidence shows this strong assumption about the arbitrariness of language is invalid. This project will use a combination of behavioural, neuroimaging and computational studies to characterise how the brain processes statistical regularities in sound-to-meaning correspondences as probabilistic cues to attain spoken language. The outcome will be a better neural account of language comprehension and production. The benefit of this new account will be a stronger basis for assessment and treatment of developmental and acquired language impairments.
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