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.

1.6K

Publications

86.6K

Citations

5.3K

Authors

1.5K

Institutions

Publications per year

2017–2026

743

Authors

5.3K

  1. LZ
    Liangpei Zhang

    Wuhan University, China

    11 publications · 2.1K citations

    11

    h-index

  2. YL
    Yuxing Li

    Xi'an University of Technology, China

    9 publications · 498 citations

    9

    h-index

  3. JR
    Jinchang Ren

    University of Strathclyde, United Kingdom

    8 publications · 554 citations

    8

    h-index

  4. HH
    Hynek Heřmanský

    Johns Hopkins University, United States

    7 publications · 458 citations

    7

    h-index

  5. LJ
    Licheng Jiao

    Xidian University, China

    7 publications · 566 citations

    7

    h-index

1–5 of 5.3K

Venues

  1. IEEE Transactions on Geoscience and Remote Sensing

    76 publications · 11.3K citations

    43

    h-index

  2. Remote Sensing

    44 publications · 1.9K citations

    26

    h-index

  3. Sensors

    34 publications · 1.1K citations

    20

    h-index

  4. 18

    h-index

  5. IEEE Geoscience and Remote Sensing Letters

    GRSL · 21 publications · 3K citations

    17

    h-index

1–5