Streamline Clustering

Streamline Clustering is a computational method in flow visualization that partitions a set of streamlines into groups based on similarity in geometric or topological characteristics to reveal coherent structures in vector fields.

14

Publications

711

Citations

47

Authors

21

Institutions

Publications per year

2017–2026

1

Authors

47

  1. DK
    David Kao

    University of Colorado Denver, United States

    2 publications · 212 citations

    2

    h-index

  2. CS
    Ching-Kuang Shene

    Michigan Technological University, United States

    2 publications · 96 citations

    2

    h-index

  3. AP
    Alex Pang

    University of California, Santa Cruz, United States

    2 publications · 212 citations

    2

    h-index

  4. HT
    Holger Theisel

    Otto-von-Guericke-Universität Magdeburg, Germany

    2 publications · 123 citations

    2

    h-index

  5. CV
    Clement Vachet

    University of Utah, United States

    1 publications · 28 citations

    1

    h-index

1–5 of 47

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 4 publications · 275 citations

    4

    h-index

  2. Data & Knowledge Engineering

    DKE · 1 publications · 30 citations

    1

    h-index

  3. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 1 publications · 13 citations

    1

    h-index

  4. 1

    h-index

  5. NeuroImage

    1 publications · 49 citations

    1

    h-index

1–5