Uncertainty Annotation

Uncertainty Annotation is a scholarly contribution in visual analytics that formalizes the systematic encoding of uncertain information within image data, distinguished by its focus on representing, structuring, and augmenting visual content with explicit uncertainty metadata to support interpretive reasoning and decision-making under uncertainty.

21

Publications

933

Citations

93

Authors

37

Institutions

Publications per year

2017–2026

11

Authors

93

  1. DD
    Dengxin Dai

    ETH Zurich, Switzerland

    3 publications · 205 citations

    3

    h-index

  2. LV
    Luc Van Gool

    ETH Zurich, Switzerland

    3 publications · 205 citations

    3

    h-index

  3. CS
    Christos Sakaridis

    ETH Zurich, Switzerland

    3 publications · 205 citations

    3

    h-index

  4. AC
    Andrej Cedilnik

    University of Maryland, Baltimore County, United States

    2 publications · 133 citations

    2

    h-index

  5. PR
    Penny Rheingans

    University of Maryland, Baltimore County, United States

    2 publications · 133 citations

    2

    h-index

1–5 of 93

Venues

  1. Computers Environment and Urban Systems

    1 publications · 67 citations

    1

    h-index

  2. 1

    h-index

  3. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 1 publications · 84 citations

    1

    h-index

  4. IEEE Visualization

    Conference · 1 publications · 78 citations

    1

    h-index

  5. 1

    h-index

1–5