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Combination of Fractional-Order Derivative and Spectral Variable Selection to Improve Soil Properties Prediction Using Vis-Nir Spectroscopy

https://doi.org/10.2139/ssrn.4778810
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inferredcites →https://doi.org/10.1007/s11368-021-02949-4openalex-extracted
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inferredcites →https://doi.org/10.1016/j.aca.2009.06.046openalex-extracted
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Combination of Convolutional Neural Networks and Recurrent Neural Networks for predicting soil properties using Vis–NIR spectroscopy
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