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ABSTRACT: This study covers 25 samples of lateritic materials, in the following granular classes (0/20, 0/25, 0/31.5, 0/40 and 0/50 mm). The samples are taken from the borrow pits of Lam-Lam, Mont ...
Abstract: Soil is a vital resource for various industries, including agriculture, engineering, and manufacturing, where accurate in-situ classification is essential for a wide range of applications.
Abstract: The study presents a novel use of Convolutional Neural Network (CNN) algorithms for crop prediction and soil type classification. Soil type classification is crucial for agricultural ...
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