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Hyperspectral and SAR Image Classification via Multiscale Interactive Fusion Network

IEEE Transactions on Neural Networks and Learning Systems

Junjie Wang, Wei Li, Yunhao Gao, Mengmeng Zhang, Ran Tao, Qian Du

Citations:

104

References:

46

Abstract
Due to the limitations of single-source data, joint classification using multisource remote sensing data has received increasing attention. However, existing methods still have certain shortcomings when faced with feature extraction from single-source data and feature fusion between multisource data. In this article, a method based on multiscale interactive information extraction (MIFNet) for hype...
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Keywords
Fuse (electrical)
Computer science
Hyperspectral imaging
Synthetic aperture radar
Data mining
Block (permutation group theory)
Artificial intelligence
Feature extraction
Range (aeronautics)
Feature (linguistics)
Sensor fusion
Pattern recognition (psychology)
Linguistics
Philosophy
Materials science
Geometry
Mathematics
Electrical engineering
Composite material
Engineering
Sustainable Development Goals (SDG)
Industry, innovation and infrastructure
2022
Article
Institution

Beijing Key Laboratory of Fractional Signals and Systems and the School of Information and Electronics, Beijing Institute of Technology, Beijing, China, 

Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA

Publisher

Institute of Electrical and Electronics Engineers

2-Y Citation Average

7.775

DOI

https://doi.org/10.1109/tnnls.2022.3171572

Language

en

Country

China, 

United States

Hyperspectral and SAR Image Classification via Multiscale Interactive Fusion Network

Hyperspectral and SAR Image Classification via Multiscale Interactive Fusion Network

IEEE Transactions on Neural Networks and Learning Systems

Junjie Wang, Wei Li, Yunhao Gao, Mengmeng Zhang, Ran Tao, Qian Du

Citations:

104

References:

46

Abstract
Due to the limitations of single-source data, joint classification using multisource remote sensing data has received increasing attention. However, existing methods still have certain shortcomings when faced with feature extraction from single-source data and feature fusion between multisource data. In this article, a method based on multiscale interactive information extraction (MIFNet) for hype...
See More
Keywords
Fuse (electrical)
Computer science
Hyperspectral imaging
Synthetic aperture radar
Data mining
Block (permutation group theory)
Artificial intelligence
Feature extraction
Range (aeronautics)
Feature (linguistics)
Sensor fusion
Pattern recognition (psychology)
Linguistics
Philosophy
Materials science
Geometry
Mathematics
Electrical engineering
Composite material
Engineering
Sustainable Development Goals (SDG)
Industry, innovation and infrastructure
2022
Article
Institution

Beijing Key Laboratory of Fractional Signals and Systems and the School of Information and Electronics, Beijing Institute of Technology, Beijing, China, 

Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA

Publisher

Institute of Electrical and Electronics Engineers

2-Y Citation Average

7.775

DOI

https://doi.org/10.1109/tnnls.2022.3171572

Language

en

Country

China, 

United States