Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Automatic annotation of coral reefs using deep learning

    Access Status
    Fulltext not available
    Authors
    Mahmood, A.
    Bennamoun, M.
    An, Senjian
    Sohel, F.
    Boussaid, F.
    Hovey, R.
    Kendrick, G.
    Fisher, R.
    Date
    2016
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Mahmood, A. and Bennamoun, M. and An, S. and Sohel, F. and Boussaid, F. and Hovey, R. and Kendrick, G. et al. 2016. Automatic annotation of coral reefs using deep learning.
    Source Title
    OCEANS 2016 MTS/IEEE Monterey, OCE 2016
    DOI
    10.1109/OCEANS.2016.7761105
    ISBN
    9781509015375
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/70098
    Collection
    • Curtin Research Publications
    Abstract

    © 2016 IEEE. Healthy coral reefs play a vital role in maintaining biodiversity in tropical marine ecosystems. Deep sea exploration and imaging have provided us with a great opportunity to look into the vast and complex marine ecosystems. Data acquisition from the coral reefs has facilitated the scientific investigation of these intricate ecosystems. Millions of digital images of the sea floor have been collected with the help of Remotely Operated Vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs). Automated technology to monitor the health of the oceans allows for transformational ecological outcomes by standardizing methods for detecting and identifying species. Manual annotation is a tediously repetitive and a time consuming task for marine experts. It takes 10-30 minutes for a marine expert to meticulously annotate a single image. This paper aims to automate the analysis of large available AUV imagery by developing advanced deep learning tools for rapid and large-scale automatic annotation of marine coral species. Such an automated technology would greatly benefit marine ecological studies in terms of cost, speed, accuracy and thus in better quantifying the level of environmental change marine ecosystems can tolerate. We propose a deep learning based classification method for coral reefs. We also report the application of the proposed technique towards the automatic annotation of unlabelled mosaics of the coral reef in the Abrolhos Islands, Western Australia. Our proposed method automatically quantifies the coral coverage in this region and detects a decreasing trend in coral population which is in line with conclusions by marine ecologists.

    Related items

    Showing items related by title, author, creator and subject.

    • Deep Image Representations for Coral Image Classification
      Mahmood, A.; Bennamoun, M.; An, Senjian; Sohel, F.; Boussaid, F.; Hovey, R.; Kendrick, G.; Fisher, R. (2018)
      Healthy coral reefs play a vital role in maintaining biodiversity in tropical marine ecosystems. Remote imaging techniques have facilitated the scientific investigations of these intricate ecosystems, particularly at ...
    • Mesophotic depths as refuge areas for fishery-targeted species on coral reefs
      Lindfield, S.; Harvey, Euan; Halford, A.; McIlwain, Jennifer (2016)
      Coral reefs are subjected to unprecedented levels of disturbance with population growth and climate change combining to reduce standing coral cover and stocks of reef fishes. Most of the damage is concentrated in shallow ...
    • Functionally diverse reef-fish communities ameliorate coral disease
      Raymundo, L.; Halford, Andy; Maypa, A.; Kerr, A. (2009)
      Coral reefs, the most diverse of marine ecosystems, currently experience unprecedented levels of degradation. Diseases are now recognized as a major cause of mortality in reef-forming corals and are complicit in phase ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.