SSTNT: A Spatial–Spectral Similarity Guided Transformer-in-Transformer for Hyperspectral Unmixing

Vision Transformers (ViTs), owing to their strong capability in modeling global contextual dependencies, have been widely adopted in hyperspectral image unmixing (HU). However, standard ViTs process images by partitioning them into non-overlapping patches, which disrupts spatial continuity at the pi...

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Bibliografiska uppgifter

Huvudupphov:	Xinyu Cui, Xinyue Zhang, Aoran Dai, Da Sun
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2026-03-01
Serie:	Photonics
Ämnen:	hyperspectral unmixing (HU) transformer Transformer-in-Transformer multi-head self-attention mechanism linear self-attention mechanism
Länkar:	https://www.mdpi.com/2304-6732/13/3/276
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