Land classification is crucial for environmental monitoring, resource management, and urban planning. This research explores using Kolmogorov-Arnold Networks (KAN), a novel machine learning model, for multispectral land classification. Unlike traditional neural networks, KAN utilizes univariate functions as activation mechanisms, enhancing its ability to capture complex spatial and spectral patterns in satellite imagery. The study focuses […]
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