TEBS: Temperature–Emissivity–Driven band selection for thermal infrared hyperspectral image classification with structured State-Space model and gated attention

Thermal infrared hyperspectral images (TIR-HSIs) provide unique spectral insights that are often unattainable with visible imagery, making them invaluable for applications such as land cover classification and geological mapping. However, the high spectral redundancy in TIR-HSIs often leads to incre...

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Bibliografiske detaljer

Principais autores:	Enyu Zhao, Nianxin Qu, Yulei Wang, Caixia Gao, Jian Zeng
Format:	Artigo
Sprog:	Inglês
Udgivet:	Elsevier 2025-08-01
Serier:	International Journal of Applied Earth Observations and Geoinformation
Fag:	Thermal infrared Unsupervised methods Hyperspectral image classification Band selection Transformer network
Online adgang:	http://www.sciencedirect.com/science/article/pii/S1569843225003577
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