Hybrid-KANet: a hyperspectral remote sensing crop classification method based on the Kolmogorov–Arnold network

Hyperspectral remote sensing crop classification is crucial in precision agriculture management. However, existing studies are usually difficult to adequately model the complex nonlinear feature distributions in hyperspectral data, which often limits the classification performance and affects the re...

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Bibliographic Details

Published in:	Geo-spatial Information Science
Main Authors:	Weizhen Zhang, Zhihui Li, Tong Zhen
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2025-08-01
Subjects:	Crop classification deep learning GIS hyperspectral remote sensing Kolmogorov-Arnold network (KAN) precision agriculture
Online Access:	https://www.tandfonline.com/doi/10.1080/10095020.2025.2538831