Cluster Number Selection

Cluster Number Selection is a methodological process in spatial clustering that determines the optimal number of clusters by distinguishing underlying spatial patterns from noise through statistical, computational, or heuristic criteria.

282

Publications

24K

Citations

1K

Authors

417

Institutions

Publications per year

2017–2026

91

Authors

1K

  1. YC
    Yiu‐ming Cheung

    Hong Kong Baptist University, Hong Kong SAR China

    4 publications · 490 citations

    4

    h-index

  2. JL
    Jialei Liu

    Anyang Normal University, China

    3 publications · 457 citations

    3

    h-index

  3. MC
    Malika Charrad

    Centre d'études et de recherche en informatique et communications, France

    3 publications · 2.9K citations

    3

    h-index

  4. WW
    Wen Wang

    Kunming University of Science and Technology, China

    3 publications · 457 citations

    3

    h-index

  5. YB
    Younès Bennani

    Université Sorbonne Paris Nord, France

    3 publications · 64 citations

    3

    h-index

1–5 of 1K

Venues

  1. Pattern Recognition

    6 publications · 1K citations

    6

    h-index

  2. IEEE Access

    6 publications · 178 citations

    6

    h-index

  3. Pattern Recognition Letters

    5 publications · 393 citations

    5

    h-index

  4. Procedia Computer Science

    5 publications · 172 citations

    5

    h-index

  5. IEEE Transactions on Neural Networks

    3 publications · 273 citations

    3

    h-index

1–5