Segmentation Model Evaluation

Segmentation Model Evaluation is a methodological framework within the field of data analytics that systematically assesses the performance, accuracy, and robustness of segmentation models by applying quantitative metrics and validation techniques to determine their effectiveness in partitioning data into meaningful and distinct groups.

386

Publications

25.8K

Citations

2K

Authors

804

Institutions

Publications per year

2017–2026

256

Authors

2K

  1. SK
    Simon K. Warfield

    Harvard University, United States

    5 publications · 2.3K citations

    5

    h-index

  2. SB
    Shunxing Bao

    Vanderbilt University, United States

    3 publications · 183 citations

    3

    h-index

  3. AK
    Arjan Kuijper

    Fraunhofer Institute for Computer Graphics Research, Germany

    3 publications · 93 citations

    3

    h-index

  4. KH
    Kelly H. Zou

    Brigham and Women's Hospital, United States

    3 publications · 1.9K citations

    3

    h-index

  5. YH
    Yuankai Huo

    Vanderbilt University, United States

    3 publications · 183 citations

    3

    h-index

1–5 of 2K

Venues

  1. arXiv (Cornell University)

    Repository · 15 publications · 581 citations

    14

    h-index

  2. Scientific Reports

    10 publications · 730 citations

    10

    h-index

  3. IEEE Access

    9 publications · 473 citations

    9

    h-index

  4. Pattern Recognition Letters

    7 publications · 744 citations

    7

    h-index

  5. Pattern Recognition

    7 publications · 1.6K citations

    7

    h-index

1–5