Multilinear hyperspectral unmixing based on autoencoder and recurrent neural network

Spectral unmixing techniques estimate the endmember spectra and corresponding abundance fractions that constitute the pixels of hyperspectral remote sensing images, revealing the mixing mechanisms of materials within pixels. In recent years, deep learning has shown significant potential in advancing...

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Vydané v:	Applied soft computing Ročník 185; s. 113972
Hlavní autori:	Jin, Zehui, Yi, Xiaorui, Liu, Yue, Zhang, Hongjuan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.12.2025
Predmet:	Autoencoder network Hyperspectral image Nonlinear spectral unmixing Recurrent neural network Nonlinear spectral unmixing Recurrent neural network Hyperspectral image Autoencoder network
ISSN:	1568-4946
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