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    Automatic Detectors for Underwater Soundscape Measurements

    246385_Madhusudhana S 2015.pdf (12.43Mb)
    Access Status
    Open access
    Authors
    Madhusudhana, Shyam Kumar
    Date
    2015
    Supervisor
    Dr Christine Erbe
    Assoc. Prof. Alexander Gavrilov
    Type
    Thesis
    Award
    PhD
    
    Metadata
    Show full item record
    School
    Department of Physics and Astronomy, Centre for Marine Science and Technology
    URI
    http://hdl.handle.net/20.500.11937/649
    Collection
    • Curtin Theses
    Abstract

    Environmental impact regulations require that marine industrial operators quantify their contribution to underwater noise scenes. Automation of such assessments becomes feasible with the successful categorisation of sounds into broader classes based on source types – biological, anthropogenic and physical. Previous approaches to passive acoustic monitoring have mostly been limited to a few specific sources of interest. In this study, source-independent signal detectors are developed and a framework is presented for the automatic categorisation of underwater sounds into the aforementioned classes.

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