A Multiscale Dual-Branch Feature Fusion and Attention Network for Hyperspectral Images Classification

A Multiscale Dual-Branch Feature Fusion and Attention Network for Hyperspectral Images Classification

Recently, hyperspectral image classification based on deep learning has achieved considerable attention. Many convolutional neural network classification methods have emerged and exhibited superior classification performance. However, most methods focus on extracting features by using fixed convolut...

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Bibliographic Details
Main Authors: Hongmin Gao, Yiyan Zhang, Zhonghao Chen, Chenming Li
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
dual-branch feature fusion (DBFM)
hyperspectral image (HSI) classification
multiscale feature extraction (MSFE) module
shuffle attention block
Online Access:https://ieeexplore.ieee.org/document/9512469/

Internet

https://ieeexplore.ieee.org/document/9512469/

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