Spatial-Channel Multiscale Transformer Network for Hyperspectral Unmixing

In recent years, deep learning (DL) has been demonstrated remarkable capabilities in hyperspectral unmixing (HU) due to its powerful feature representation ability. Convolutional neural networks (CNNs) are effective in capturing local spatial information, but limited in modeling long-range dependenc...

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Autori principali:	Haixin Sun, Qiuguang Cao, Fanlei Meng, Jingwen Xu, Mengdi Cheng
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2025-07-01
Serie:	Sensors
Soggetti:	global contextual information multiscale transformer hyperspectral unmixing spatial–spectral modeling multi-head self-attention
Accesso online:	https://www.mdpi.com/1424-8220/25/14/4493
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