Low-Rank Constrained Attention-Enhanced Multiple Spatial–Spectral Feature Fusion for Small Sample Hyperspectral Image Classification

Low-Rank Constrained Attention-Enhanced Multiple Spatial–Spectral Feature Fusion for Small Sample Hyperspectral Image Classification

Hyperspectral images contain rich features in both spectral and spatial domains, which bring opportunities for accurate recognition of similar materials and promote various fine-grained remote sensing applications. Although deep learning models have been extensively investigated in the field of hype...

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Bibliographic Details
Main Authors: Fan Feng, Yongsheng Zhang, Jin Zhang, Bing Liu
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Remote Sensing
Subjects:
hyperspectral image classification
factor analysis
attention-enhanced spatial–spectral feature learning
coordinate attention
low-rank second-order pooling
Online Access:https://www.mdpi.com/2072-4292/15/2/304

Internet

https://www.mdpi.com/2072-4292/15/2/304

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