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    Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG)

    Access Status
    Fulltext not available
    Authors
    Sivarajah, Y.
    Holden, E.
    Kovesi, P.
    Togneri, R.
    Tan, Tele
    Price, G.
    Date
    2012
    Type
    Conference Paper
    
    Metadata
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    Citation
    Sivarajah, Y. and Holden, E. and Kovesi, P. and Togneri, R. and Tan, T. and Price, G. 2012. Studying the Impact of Feature Saliency for Geoscientific Target Detection using Electroencephalography (EEG), in Proceedings of the 2012 International Conference on Digital Image Computing: Techniques and Applications (DICTA) Dec 3-5 2012. Fremantle, Western Australia: Institute of Electrical and Electronics Engineers.
    Source Title
    Proceedings of the 2012 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2012
    Source Conference
    2012 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2012
    DOI
    10.1109/DICTA.2012.6411707
    ISBN
    978-146732181-5
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/28379
    Collection
    • Curtin Research Publications
    Abstract

    Accuracy and efficiency in geoscientific data interpretation is critically important for the resource industry, as based on these interpretations, significant financial decisions are made for exploration and extraction of resources. This study aims to understand image characteristics that impact interpreters' ability to detect geological targets within magnetic geophysics images. We use the Brain Computer Interface (BCI) approach to profile interpreter's neurological responses to geophysical target images using electroencephalography (EEG). These results are compared with image saliency analysis outputs, specifically the spatial distribution of visual attention peaks. Our experimental results showed that images with a wider dispersion of saliency lead to a lower rate of target detection based on EEG activities of interpreters.

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