SpecSpatMamba: an efficient hyperspectral image classification method integrating spectral-spatial dual-path and state space model

Current hyperspectral image classification methods face three critical limitations: (1) traditional CNNs suffer from the curse of dimensionality when processing high-dimensional spectral data, leading to overfitting and poor generalization; (2) existing approaches fail to effectively address spectra...

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Veröffentlicht in:	The Egyptian journal of remote sensing and space sciences Jg. 28; H. 4; S. 628 - 644
Hauptverfasser:	Liao, Jianshang, Wang, Liguo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2025
Schlagworte:	Deep learning Hyperspectral image classification Linear computational complexity Spectral-spatial dual-path State space model Deep learning State space model Linear computational complexity Spectral-spatial dual-path Hyperspectral image classification
ISSN:	1110-9823
Online-Zugang:	Volltext
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