Spectral Feature Extraction
Spectral Feature Extraction is a feature extraction method that transforms time-domain signals into their frequency-domain representations to reveal inherent spectral characteristics, distinguishing it from other feature extraction techniques by its focus on frequency-specific patterns and energy distributions across signal spectra.
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2017–2026
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Digital Spectral Analysis with Applications.
B. Porat, S.L. Marple · Mathematics of Computation · 1988 · 2.7K citations
Graph Convolutional Networks for Hyperspectral Image Classification
Danfeng Hong, Lianru Gao, Jing Yao et al. · IEEE Transactions on Geoscience and Remote Sensing · 2020 · 1.6K citations · Full text
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Chinese Academy of Sciences
Beijing, China
25 h-index
141 publications
10.4K citations
Wuhan University
Wuhan, China
21 h-index
109 publications
11.2K citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
20 h-index
61 publications
7.8K citations
University of Chinese Academy of Sciences
Beijing, China
19 h-index
44 publications
3.5K citations

Northwestern Polytechnical University
Xi'an, China
19 h-index
66 publications
4.9K citations

Harbin Institute of Technology
Harbin, China
18 h-index
60 publications
4.2K citations

Zhejiang University
Hangzhou, China
17 h-index
53 publications
2.9K citations

Xidian University
Xi'an, China
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77 publications
6K citations
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GRSL · 21 publications · 3K citations
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