Uncertainty Classification

Uncertainty Classification is a systematic framework in scientific visualization that categorizes the diverse forms and sources of uncertainty inherent in data and visual representations according to their nature, origin, and propagation behavior.

37

Publications

1.8K

Citations

132

Authors

60

Institutions

Publications per year

2017–2026

14

Authors

132

  1. JH
    Jung-Woo Ha

    Naver (South Korea), South Korea

    2 publications · 338 citations

    2

    h-index

  2. JC
    Jonghyun Choi

    University of Maryland, College Park, United States

    2 publications · 338 citations

    2

    h-index

  3. HK
    Heesu Kim

    Naver (South Korea), South Korea

    2 publications · 338 citations

    2

    h-index

  4. JB
    Jihwan Bang

    Naver (South Korea), South Korea

    2 publications · 338 citations

    2

    h-index

  5. YY
    Youngjoon Yoo

    Seoul National University, South Korea

    2 publications · 338 citations

    2

    h-index

1–5 of 132

Venues

  1. IEEE Transactions on Cybernetics

    1 publications · 26 citations

    1

    h-index

  2. Reliability Engineering & System Safety

    1 publications · 65 citations

    1

    h-index

  3. Urban Climate

    1 publications · 24 citations

    1

    h-index

  4. Physical review. D/Physical review. D.

    PRD · 1 publications · 14 citations

    1

    h-index

  5. PeerJ Computer Science

    1 publications · 35 citations

    1

    h-index

1–5