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    Face detection from greyscale images using details from categorized wavelet coefficients as features for a dynamic supervised forward propagation network

    Access Status
    Fulltext not available
    Authors
    Yeong, L.
    Ang, L.
    Lim, Hann
    Seng, K.
    Date
    2009
    Type
    Journal Article
    
    Metadata
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    Citation
    Yeong, L. and Ang, L. and Lim, H. and Seng, K. 2009. Face detection from greyscale images using details from categorized wavelet coefficients as features for a dynamic supervised forward propagation network. International Journal of Pattern Recognition and Artificial Intelligence. 23 (1): pp. 3-15.
    Source Title
    International Journal of Pattern Recognition and Artificial Intelligence
    DOI
    10.1142/S0218001409006977
    ISSN
    0218-0014
    School
    Curtin Sarawak
    URI
    http://hdl.handle.net/20.500.11937/42759
    Collection
    • Curtin Research Publications
    Abstract

    A dynamic counterpropagation network based on the forward only counterpropagation network (CPN) is applied as the classifier for face detection. The network, called the dynamic supervised forward-propagation network (DSFPN) trains using a supervised algorithm that grows dynamically during training allowing subclasses in the training data to be learnt. The network is trained using a reduced dimensionality categorized wavelet coefficients of the image data. Experimental results obtained show that a 94% correct detection rate can be achieved with less than 6% false positives. © 2009 World Scientific Publishing Company.

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