Spectral Feature Detection

Spectral Feature Detection is a methodological approach in signal and image analysis that identifies distinctive patterns or anomalies within data by examining frequency-domain characteristics derived from spectral transformations.

374

Publications

19.8K

Citations

1.9K

Authors

702

Institutions

Publications per year

2017–2026

120

Authors

1.9K

  1. RN
    R. N. Clark

    United States Geological Survey, United States

    4 publications · 480 citations

    4

    h-index

  2. GH
    Guoquan He

    Yangtze Normal University, China

    3 publications · 51 citations

    3

    h-index

  3. WH
    Wenjiang Huang

    Chinese Academy of Sciences, China

    3 publications · 208 citations

    3

    h-index

  4. GL
    Gang Li

    Tianjin University, China

    3 publications · 51 citations

    3

    h-index

  5. HM
    Huiqin Ma

    Chinese Academy of Sciences, China

    3 publications · 208 citations

    3

    h-index

1–5 of 1.9K

Venues

  1. The Astrophysical Journal

    ApJ · 17 publications · 987 citations

    15

    h-index

  2. 12

    h-index

  3. Analytica Chimica Acta

    10 publications · 357 citations

    10

    h-index

  4. 8

    h-index

  5. Applied Spectroscopy

    8 publications · 185 citations

    8

    h-index

1–5