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    Archive for the 'Neural Networks' Category

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    MULTISPECTRAL
    CLASSIFICATION OF IRS-
    P6 IMAGES USING
    TEXTURAL FEATURES
    TRAINED SUPERVISED
    NEURAL NETWORKS
    ABSTRACT Supervised
    classification plays an
    important role in remote
    sensing image
    interpretation, in which the
    image pixels are classified
    to various predefined
    categories based on the
    spectral reflectance values
    in different bands. In
    reality some classes have
    very close spectral
    reflectance values and
    therefore they overlap in
    the feature space. This
    produces spectral
    confusion among the
    classes and results in
    inaccurate classified
    images. To remove

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    ABSTRACT
    In this paper, a new approach is suggested to grade apples based on colour and size. Two different feature extraction methods are developed using image processing techniques in a machine vision environment. The extracted feature set is used to train and test a Back propagation neural network. The graded results are compared with manually graded [...]

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