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Field of Research : Image Processing
Australian State/Territory : VIC
Australian State/Territory : NSW
Research Topic : information
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  • Funded Activity

    Linkage Projects - Grant ID: LP0667490

    Funder
    Australian Research Council
    Funding Amount
    $650,000.00
    Summary
    Data Management Technologies for the Magnetic Resonance Imaging e-Research Grid. Howard Florey Institute researchers will collaborate with SGI's file-systems engineering team. Substantial benefits are expected from the development of techniques to support centralized and distributed processing medical image datasets. Issues requiring research include file space allocation algorithms and caching strategies. The proposed rapid database access technologies aim at solving these problems in the medic .... Data Management Technologies for the Magnetic Resonance Imaging e-Research Grid. Howard Florey Institute researchers will collaborate with SGI's file-systems engineering team. Substantial benefits are expected from the development of techniques to support centralized and distributed processing medical image datasets. Issues requiring research include file space allocation algorithms and caching strategies. The proposed rapid database access technologies aim at solving these problems in the medical imaging research context. The project attempts to 'improve data management for existing and new business applications'. This enhanced sharing of information will improve critical mass therefore fostering national and international collaboration.
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    Funded Activity

    Linkage Projects - Grant ID: LP0219691

    Funder
    Australian Research Council
    Funding Amount
    $67,635.00
    Summary
    Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new appr .... Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new approach to digital video coding other than the constant bit rate coding techniques which have dominated digital video research for the past four decades. It will form a part of the theoretical foundation and principles for the next generation video coding and compression techniques, and may lead to new standards and practice.
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    Funded Activity

    Linkage Projects - Grant ID: LP120100595

    Funder
    Australian Research Council
    Funding Amount
    $145,000.00
    Summary
    A theoretical framework for practical partial fingerprint identification. Fingerprints captured from a crime scene are often partial and poor quality which makes it difficult to identify the criminal suspects from large databases. This project will find mathematical models which can estimate the missing information located in the blank areas of a partial fingerprint and effectively identify it.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200103223

    Funder
    Australian Research Council
    Funding Amount
    $396,000.00
    Summary
    Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored .... Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored to individual characteristics. The success of this project could significantly advance the fundamental research in image analysis. Expected outcomes include new knowledge and algorithms for image analysis, which could benefit fields like biology and archaeology, where labeled images are hard to attain and scarce.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190102574

    Funder
    Australian Research Council
    Funding Amount
    $380,000.00
    Summary
    Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-vi .... Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-visual services that are of great interest to international standards bodies and industry, while facilitating free interaction and augmented reality. This project will provide significant benefits to broadcast, entertainment, surveillance and health industries and position Australia as a world leader in this field.
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