Adaptive spectral-spatial feature fusion network for hyperspectral image classification using limited training samples

Adaptive spectral-spatial feature fusion network for hyperspectral image classification using limited training samples

Recently, the excellent power of spectral-spatial feature representation of convolutional neural network (CNN) has gained widespread attention for hyperspectral image (HSI) classification. Nevertheless, the practical performance of CNN-based models in HSI classification is ordinarily limited by the...

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Bibliographic Details
Main Authors: Hongmin Gao, Zhonghao Chen, Feng Xu
Format: Article
Language:English
Published: Elsevier 2022-03-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Convolutional neural network (CNN)
Hyperspectral image (HSI) classification
Spectral band non-localization (SBNL)
Multiscale-share inception block (MSIB)
Adaptive feature fusion (AFF)
Online Access:http://www.sciencedirect.com/science/article/pii/S0303243422000137

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http://www.sciencedirect.com/science/article/pii/S0303243422000137

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