Unsupervised Change Detection

Unsupervised Change Detection is a change detection paradigm that identifies significant alterations between temporal observations in the absence of labeled training data by leveraging intrinsic data structures and statistical disparities to distinguish change from background variation.

349

Publications

23K

Citations

840

Authors

336

Institutions

Publications per year

2017–2026

193

Authors

840

  1. LB
    Lorenzo Bruzzone

    University of Trento, Italy

    44 publications · 6K citations

    29

    h-index

  2. FB
    Francesca Bovolo

    University of Trento, Italy

    29 publications · 3K citations

    19

    h-index

  3. MG
    Maoguo Gong

    Xidian University, China

    18 publications · 2.1K citations

    16

    h-index

  4. TÇ
    Turgay Çelik

    University of the Witwatersrand, South Africa

    12 publications · 2K citations

    12

    h-index

  5. LJ
    Licheng Jiao

    Xidian University, China

    12 publications · 519 citations

    11

    h-index

1–5 of 840

Venues

  1. 42

    h-index

  2. IEEE Geoscience and Remote Sensing Letters

    GRSL · 42 publications · 3.7K citations

    28

    h-index

  3. 22

    h-index

  4. Remote Sensing

    22 publications · 923 citations

    17

    h-index

  5. International Journal of Remote Sensing

    19 publications · 815 citations

    16

    h-index

1–5