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In recent time, the most applied classification method for hyperspectral images is based on the supervised deep learning approach. The hyperspectral images require special handling while it consists of hundreds of bands / channels. In this article, the experiments are conducted using one of the widespread deep learning models, Convolutional Neural Networks (CNNs), specifically, Csutom Spectral CNN architecture (CSCNN). The introduced network is based on the data reduction and datadoi:10.21608/ijicis.2022.147175.1198 fatcat:sfh2vyyxmnhg7nob3pwukb7mpi