Unsupervised Image Clustering

Unsupervised Image Clustering is a machine learning approach that partitions image data into meaningful groups based on intrinsic visual similarities without relying on labeled training examples.

330

Publications

16.1K

Citations

1.1K

Authors

491

Institutions

Publications per year

2017–2026

129

Authors

1.1K

  1. HF
    Hichem Frigui

    University of Louisville, United States

    5 publications · 156 citations

    5

    h-index

  2. JM
    Joachim M. Buhmann

    ETH Zurich, Switzerland

    4 publications · 332 citations

    4

    h-index

  3. LJ
    Licheng Jiao

    Xidian University, China

    4 publications · 87 citations

    4

    h-index

  4. JM
    James M. Murphy

    Tufts University, United States

    3 publications · 97 citations

    3

    h-index

  5. AV
    Andrea Vedaldi

    University of Oxford, United Kingdom

    3 publications · 278 citations

    3

    h-index

1–5 of 1.1K

Venues

  1. arXiv (Cornell University)

    Repository · 14 publications · 953 citations

    11

    h-index

  2. 8

    h-index

  3. International Journal of Remote Sensing

    7 publications · 221 citations

    7

    h-index

  4. IEEE Geoscience and Remote Sensing Letters

    GRSL · 6 publications · 327 citations

    6

    h-index

  5. 5

    h-index

1–5