Cross-scale Mixing Attention for Multisource Remote Sensing Data Fusion and Classification

Hyperspectral and multispectral images (HS/MS) fusion and classification as an important branch of data quality improvement and interpretation, has attracted increasing attention in recent years. However, the unavailable sensor prior still limits the performance of many traditional fusion methods, c...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2023-01, Vol.61, p.1-1
Hauptverfasser:	Gao, Yunhao, Zhang, Mengmeng, Wang, Junjie, Li, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Classification Convolutional neural networks cross-scale mixing attention transformer (CSMFormer) data fusion Data integration Feature extraction Hyperspectral and multispectral images Image reconstruction Image segmentation land-covers classification long-range dependencies Mixers Multiaccess communication Multisensor fusion Neural networks Quality control Remote sensing Transformers
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