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Showing 1 to 2 of 2 for “"Visual feature selection"”.

  1. WAVELENGTH AND VISUAL FEATURE SELECTION FOR NON-DESTRUCTIVE EVALUATION OF FUSARIUM HEAD BLIGHT IN WHEAT USING HYPERSPECTRAL IMAGING

    … models trained on spatial–spectral features. The scanner captured hyperspectral scans of over 1,500 healthy and Fusarium-damaged kernels, from which statistical features were extracted at each wavelength. Classification models were trained to assess the contribution of individual …

    sask Repository record for WAVELENGTH AND VISUAL FEATURE SELECTION FOR NON-DESTRUCTIVE EVALUATION OF FUSARIUM HEAD BLIGHT IN WHEAT USING HYPERSPECTRAL IMAGING (opens in a new tab)

  2. Feature selection through visualisation for the classification of online reviews

    The purpose of this work is to prove that the visualization is at least as powerful as the best automatic feature selection algorithms. This is achieved by applying our visualization technique to the online review classification into fake and genuine reviews. Our technique uses radial chart and …

    iupui Repository record for Feature selection through visualisation for the classification of online reviews (opens in a new tab)