ARDC Research Link Australia Research Link Australia   BETA Research
Link
Australia
  • ARDC Newsletter Subscribe
  • Contact Us
  • Home
  • About
  • Feedback
  • Explore Collaborations
  • Researcher
  • Funded Activity
  • Organisation
  • Researcher
  • Funded Activity
  • Organisation
  • Researcher
  • Funded Activity
  • Organisation

Need help searching? View our Search Guide.

Advanced Search

Current Selection
Research Topic : NEURAL NETWORK
Field of Research : Computer-Human Interaction
Australian State/Territory : NSW
Clear All
Filter by Field of Research
Computer-Human Interaction (6)
Neural, Evolutionary and Fuzzy Computation (6)
Artificial Intelligence and Image Processing (4)
Adaptive Agents and Intelligent Robotics (2)
Information Systems (2)
Human Information Behaviour (1)
Interorganisational Information Systems and Web Services (1)
Filter by Socio-Economic Objective
Application Software Packages (excl. Computer Games) (4)
Expanding Knowledge in the Information and Computing Sciences (4)
Electronic Information Storage and Retrieval Services (1)
Expanding Knowledge in Engineering (1)
Information Processing Services (incl. Data Entry and Capture) (1)
Multimodal Transport (1)
Filter by Funding Provider
Australian Research Council (6)
Filter by Status
Closed (4)
Active (2)
Filter by Scheme
Discovery Projects (4)
Linkage Projects (2)
Filter by Country
Australia (6)
Filter by Australian State/Territory
NSW (6)
ACT (1)
VIC (1)
  • Researchers (8)
  • Funded Activities (6)
  • Organisations (7)
  • Funded Activity

    Linkage Projects - Grant ID: LP140100995

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin .... Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.
    Read more Read less
    More information
    Funded Activity

    Discovery Projects - Grant ID: DP180100656

    Funder
    Australian Research Council
    Funding Amount
    $366,663.00
    Summary
    Cognitive intelligent information processing and presentation in navigation. This project aims to develop a personalised navigation system to provide effective augmented-reality (AR)-based support information, built on different navigation preference and the momentary cognitive workload of the user. This will immediately encourage users to become aware of their surroundings and continuous use will facilitate the development of navigation skills. It is expected that this research will advance sci .... Cognitive intelligent information processing and presentation in navigation. This project aims to develop a personalised navigation system to provide effective augmented-reality (AR)-based support information, built on different navigation preference and the momentary cognitive workload of the user. This will immediately encourage users to become aware of their surroundings and continuous use will facilitate the development of navigation skills. It is expected that this research will advance scientific knowledge about individual differences in navigation ability. It will significantly enhance spatial learning and alleviate the apparent decline in navigational ability experienced across the life span, benefiting the aged population in Australia by enabling them to live longer independent lives.
    Read more Read less
    More information
    Funded Activity

    Linkage Projects - Grant ID: LP120200305

    Funder
    Australian Research Council
    Funding Amount
    $510,000.00
    Summary
    An integrated and real-time passenger travel and public transport service information system. This project will help the Department of Transport provide improved services to the public through a better understanding of journey planning demands in comparison to public transport services. By integrating research through design methods with technological solutions, the project will deliver better quality of service and higher customer satisfaction.
    More information
    Active Funded Activity

    Discovery Projects - Grant ID: DP220100803

    Funder
    Australian Research Council
    Funding Amount
    $490,000.00
    Summary
    AI-Human Empowered Team Decision-Making. This project aims to introduce machine intelligence into human team decision-making using the brain-to-brain synchrony that arises when people cooperate toward achieving a goal. The expected outcomes are models and indicators of this synchrony, and methods to fuse individual human decisions with autonomous machine agents, into collective decisions. This new knowledge is expected to greatly increase our understanding of cooperative decision-making by human .... AI-Human Empowered Team Decision-Making. This project aims to introduce machine intelligence into human team decision-making using the brain-to-brain synchrony that arises when people cooperate toward achieving a goal. The expected outcomes are models and indicators of this synchrony, and methods to fuse individual human decisions with autonomous machine agents, into collective decisions. This new knowledge is expected to greatly increase our understanding of cooperative decision-making by humans and machine agents. The tools produced are expected to provide a computational basis for human-autonomy teaming, the core of Industry 5.0, that software developers and end-users in various industries could further build upon to optimise complex decision-making to benefit humanity.
    Read more Read less
    More information
    Active Funded Activity

    Discovery Projects - Grant ID: DP210101093

    Funder
    Australian Research Council
    Funding Amount
    $451,737.00
    Summary
    Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. Th .... Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. The model and algorithms are intended to be integrated into an innovative brain-robot interface for field testing in a real-world industrial task. Translation of the outcomes to industry is expected to produce substantial economic and societal benefits through improved productivity and safety.
    Read more Read less
    More information
    Funded Activity

    Discovery Projects - Grant ID: DP180100670

    Funder
    Australian Research Council
    Funding Amount
    $354,592.00
    Summary
    A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general fra .... A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general framework to facilitate human-machine interaction and enable better collaborative decisions in HMAS. The outcomes will benefit human-centric automation systems in general and next-generation autonomous vehicles in particular, which will contribute to the Australian economy.
    Read more Read less
    More information

    Showing 1-6 of 6 Funded Activites

    Advanced Search

    Advanced search on the Researcher index.

    Advanced search on the Funded Activity index.

    Advanced search on the Organisation index.

    National Collaborative Research Infrastructure Strategy

    The Australian Research Data Commons is enabled by NCRIS.

    ARDC CONNECT NEWSLETTER

    Subscribe to the ARDC Connect Newsletter to keep up-to-date with the latest digital research news, events, resources, career opportunities and more.

    Subscribe

    Quick Links

    • Home
    • About Research Link Australia
    • Product Roadmap
    • Documentation
    • Disclaimer
    • Contact ARDC

    We acknowledge and celebrate the First Australians on whose traditional lands we live and work, and we pay our respects to Elders past, present and emerging.

    Copyright © ARDC. ACN 633 798 857 Terms and Conditions Privacy Policy Accessibility Statement
    Top
    Quick Feedback