Training Sample Selection

Training Sample Selection is the systematic process of identifying and acquiring representative geographic instances from a land cover dataset to optimize the calibration of classification models in remote sensing.

435

Publications

35K

Citations

1.7K

Authors

680

Institutions

Publications per year

2017–2026

209

Authors

1.7K

  1. DT
    Devis Tuia

    École Polytechnique Fédérale de Lausanne, Switzerland

    6 publications · 1.3K citations

    6

    h-index

  2. DA
    D. A. Landgrebe

    Purdue University West Lafayette, United States

    5 publications · 861 citations

    5

    h-index

  3. XH
    Xian‐Sheng Hua

    Microsoft Research Asia (China), China

    3 publications · 121 citations

    3

    h-index

  4. CC
    Chein‐I Chang

    University of Maryland, Baltimore County, United States

    3 publications · 71 citations

    3

    h-index

  5. AD
    Adam D. Myers

    University of Wyoming, United States

    3 publications · 197 citations

    3

    h-index

1–5 of 1.7K

Venues

  1. 19

    h-index

  2. Remote Sensing

    25 publications · 1.9K citations

    19

    h-index

  3. arXiv (Cornell University)

    Repository · 11 publications · 321 citations

    11

    h-index

  4. IEEE Access

    10 publications · 495 citations

    10

    h-index

  5. IEEE Geoscience and Remote Sensing Letters

    GRSL · 7 publications · 224 citations

    7

    h-index

1–5