Region-based Querying

Region-Based Querying is a visual querying paradigm that enables users to specify spatial regions of interest within an image or visual dataset as the primary means of retrieving or analyzing content, distinguishing it from holistic or object-centric querying approaches by focusing on localized, user-defined image areas.

29

Publications

4.8K

Citations

76

Authors

41

Institutions

Publications per year

2017–2026

1

Authors

76

  1. FH
    F. Hill

    University of Massachusetts Amherst, United States

    2 publications · 61 citations

    2

    h-index

  2. SC
    Shih‐Fu Chang

    Columbia University, United States

    2 publications · 162 citations

    2

    h-index

  3. BM
    B.S. Manjunath

    University of California, Santa Barbara, United States

    2 publications · 954 citations

    2

    h-index

  4. FG
    Fuwen Gao

    University of Maine, United States

    2 publications · 61 citations

    2

    h-index

  5. SE
    Sheldon E. Walker

    Beijing Normal University, China

    2 publications · 61 citations

    2

    h-index

1–5 of 76

Venues

  1. Journal of Computer and System Sciences

    2 publications · 98 citations

    2

    h-index

  2. Journal of Visual Languages & Computing

    JVLC · 1 publications · 18 citations

    1

    h-index

  3. Computer Vision and Image Understanding

    CVIU · 1 publications · 174 citations

    1

    h-index

  4. Knowledge and Information Systems

    1 publications · 35 citations

    1

    h-index

  5. 1

    h-index

1–5