Segmentation Evaluation Metrics

Segmentation Evaluation Metrics is a methodological framework that quantifies the accuracy and effectiveness of text segmentation algorithms by comparing their output against ground truth partitions using specialized coherence, boundary detection, and similarity measures.

362

Publications

24.5K

Citations

1.5K

Authors

657

Institutions

Publications per year

2017–2026

176

Authors

1.5K

  1. BG
    Basilis Gatos

    National Centre of Scientific Research "Demokritos", Greece

    10 publications · 631 citations

    10

    h-index

  2. AA
    Apostolos Antonacopoulos

    University of Salford, United Kingdom

    7 publications · 255 citations

    7

    h-index

  3. NS
    Nikolaos Stamatopoulos

    National Centre of Scientific Research "Demokritos", Greece

    6 publications · 456 citations

    6

    h-index

  4. CL
    Chew Lim Tan

    National University of Singapore, Singapore

    5 publications · 192 citations

    5

    h-index

  5. SO
    Sébastien Ourselin

    University College London, United Kingdom

    4 publications · 824 citations

    4

    h-index

1–5 of 1.5K

Venues

  1. arXiv (Cornell University)

    Repository · 17 publications · 480 citations

    15

    h-index

  2. 10

    h-index

  3. IEEE Access

    10 publications · 557 citations

    10

    h-index

  4. IEEE Transactions on Medical Imaging

    6 publications · 608 citations

    6

    h-index

  5. IEEE Transactions on Image Processing

    6 publications · 396 citations

    6

    h-index

1–5