Pattern Matching In Visual Data

Pattern Matching in Visual Data is a computational method that identifies and localizes specific structures, shapes, or arrangements within visual datasets by comparing them against predefined templates or learned models, distinguishing it from general image analysis through its focus on precise correspondence and spatial coherence.

24

Publications

3.5K

Citations

56

Authors

37

Institutions

Publications per year

2017–2026

2

Authors

56

  1. CC
    Chidambaram Chidambaram

    Universidade do Estado de Santa Catarina, Brazil

    1 publications · 17 citations

    1

    h-index

  2. PK
    Philip K. Robertson

    Commonwealth Scientific and Industrial Research Organisation, Australia

    1 publications · 70 citations

    1

    h-index

  3. PM
    Paula M. Castro

    Universidade da Coruña, Spain

    1 publications · 10 citations

    1

    h-index

  4. LW
    Lior Wolf

    Tel Aviv University, Israel

    1 publications · 23 citations

    1

    h-index

  5. SZ
    Song‐Chun Zhu

    University of California, Los Angeles, United States

    1 publications · 23 citations

    1

    h-index

1–5 of 56

Venues

  1. 3

    h-index

  2. Review of Scientific Instruments

    1 publications · 10 citations

    1

    h-index

  3. Pattern Recognition Letters

    1 publications · 18 citations

    1

    h-index

  4. International Journal of Natural Computing Research

    IJNCR · 1 publications · 17 citations

    1

    h-index

  5. Machine Vision and Applications

    1 publications · 23 citations

    1

    h-index

1–5