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    ARTICLE

    Automated Deep Learning Driven Crop Classification on Hyperspectral Remote Sensing Images

    Mesfer Al Duhayyim1,*, Hadeel Alsolai2, Siwar Ben Haj Hassine3, Jaber S. Alzahrani4, Ahmed S. Salama5, Abdelwahed Motwakel6, Ishfaq Yaseen6, Abu Sarwar Zamani6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3167-3181, 2023, DOI:10.32604/cmc.2023.033054

    Abstract Hyperspectral remote sensing/imaging spectroscopy is a novel approach to reaching a spectrum from all the places of a huge array of spatial places so that several spectral wavelengths are utilized for making coherent images. Hyperspectral remote sensing contains acquisition of digital images from several narrow, contiguous spectral bands throughout the visible, Thermal Infrared (TIR), Near Infrared (NIR), and Mid-Infrared (MIR) regions of the electromagnetic spectrum. In order to the application of agricultural regions, remote sensing approaches are studied and executed to their benefit of continuous and quantitative monitoring. Particularly, hyperspectral images (HSI) are considered the precise for agriculture as they… More >

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