Deep Attention-Guided Spatial–Spectral Network for Hyperspectral Image Unmixing-Reference-Cited by-同舟云学术

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Deep Attention-Guided Spatial–Spectral Network for Hyperspectral Image Unmixing

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Qi Lin¹^ORCID,Yue Mengyi¹^ORCID,Gao Feng¹^ORCID,Cao Bing²^ORCID,Dong Junyu¹^ORCID,Gao Xinbo³^ORCID

Affiliation:

1. School of Computer Science and Technology, Ocean University of China, Qingdao, China

2. College of Intelligence and Computing, Tianjin University, Tianjin, China

3. Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10371391.pdf?arnumber=10371391

Reference19 articles.

1. Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

2. BS³LNet: A New Blind-Spot Self-Supervised Learning Network for Hyperspectral Anomaly Detection

3. Vertex component analysis: a fast algorithm to unmix hyperspectral data

4. Hyperspectral Unmixing via $L_{1/2}$ Sparsity-Constrained Nonnegative Matrix Factorization

5. Spectral Unmixing via Data-Guided Sparsity

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dual-Stream Attention Network for Hyperspectral Image Unmixing;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

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