Hadeel Alsolai1, Mohammed Rizwanullah2,*, Mashael Maashi3, Mahmoud Othman4, Amani A. Alneil2, Amgad Atta Abdelmageed2
CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 975-992, 2023, DOI:10.32604/cmc.2023.037936
Abstract Soil classification is one of the emanating topics and major concerns in many countries. As the population has been increasing at a rapid pace, the demand for food also increases dynamically. Common approaches used by agriculturalists are inadequate to satisfy the rising demand, and thus they have hindered soil cultivation. There comes a demand for computer-related soil classification methods to support agriculturalists. This study introduces a Gradient-Based Optimizer and Deep Learning (DL) for Automated Soil Classification (GBODL-ASC) technique. The presented GBODL-ASC technique identifies various kinds of soil using DL and computer vision approaches. In the presented GBODL-ASC technique, three major… More >
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