Anomaly Visualization

Anomaly Visualization is a time-series visualization technique that specifically highlights deviations from expected patterns by integrating visual encodings to distinguish irregular data points from normal behavior.

114

Publications

4.7K

Citations

376

Authors

144

Institutions

Publications per year

2017–2026

38

Authors

376

  1. NC
    Nan Cao

    Tongji University, China

    6 publications · 465 citations

    6

    h-index

  2. MR
    Maria Riveiro

    University of Skövde, Sweden

    6 publications · 192 citations

    6

    h-index

  3. DA
    Daniel A. Keim

    University of Konstanz, Germany

    5 publications · 237 citations

    5

    h-index

  4. EK
    Eamonn Keogh

    University of California, Riverside, United States

    5 publications · 339 citations

    5

    h-index

  5. LS
    Lei Shi

    Chinese Academy of Sciences, China

    4 publications · 62 citations

    4

    h-index

1–5 of 376

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 10 publications · 823 citations

    10

    h-index

  2. 3

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 55 citations

    3

    h-index

  4. Geophysics

    2 publications · 99 citations

    2

    h-index

  5. Knowledge-Based Systems

    2 publications · 53 citations

    2

    h-index

1–5