ReSC-net: Hyperspectral Image Classification Based on Attention-Enhanced Residual Module and Spatial-Channel Attention-Reference-Cited by-同舟云学术

ReSC-net: Hyperspectral Image Classification Based on Attention-Enhanced Residual Module and Spatial-Channel Attention

Published:2024 Issue: Volume:62 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Fu Chuan¹^ORCID,Du Bo²^ORCID,Zhang Liangpei³^ORCID

Affiliation:

1. College of Computer Science, Chongqing University, Chongqing, China

2. Hubei Key Laboratory of Multimedia and Network Communication Engineering, School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Wuhan University, Wuhan, China

3. Aerospace Information Research Institute, Henan Academy of Science, Henan, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10534107.pdf?arnumber=10534107

Reference50 articles.

1. An Iterative GLRT for Hyperspectral Target Detection Based on Spectral Similarity and Spatial Connectivity Characteristics

2. Multiscale Diff-Changed Feature Fusion Network for Hyperspectral Image Change Detection

3. HyperNet: Self-Supervised Hyperspectral Spatial–Spectral Feature Understanding Network for Hyperspectral Change Detection

4. Hyperspectral image-based vegetation index (HSVI): A new vegetation index for urban ecological research

5. An Adaptive Mean-Shift Analysis Approach for Object Extraction and Classification From Urban Hyperspectral Imagery

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