Segmentation Uncertainty

Segmentation Uncertainty is a type of geospatial uncertainty that arises from the inherent ambiguity and variability in delineating spatial entities or regions during image or spatial data partitioning, distinguishing it from other geospatial uncertainties by specifically reflecting the lack of confidence in boundary placement and class assignment within segmentation processes.

82

Publications

4K

Citations

410

Authors

218

Institutions

Publications per year

2017–2026

54

Authors

410

  1. YG
    Yarin Gal

    University of Oxford, United Kingdom

    2 publications · 66 citations

    2

    h-index

  2. QG
    Qiqi Gu

    Shanghai Jiao Tong University, China

    2 publications · 85 citations

    2

    h-index

  3. TL
    Tiger Lao

    Chan Zuckerberg Initiative (United States), United States

    2 publications · 39 citations

    2

    h-index

  4. SV
    Shruthi VijayKumar

    Chan Zuckerberg Initiative (United States), United States

    2 publications · 39 citations

    2

    h-index

  5. EH
    Eduardo Hirata-Miyasaki

    Chan Zuckerberg Initiative (United States), United States

    2 publications · 39 citations

    2

    h-index

1–5 of 410

Venues

  1. Medical Image Analysis

    6 publications · 519 citations

    6

    h-index

  2. IEEE Access

    5 publications · 188 citations

    5

    h-index

  3. Neural Computing and Applications

    2 publications · 93 citations

    2

    h-index

  4. Computers in Biology and Medicine

    2 publications · 75 citations

    2

    h-index

  5. Knowledge-Based Systems

    2 publications · 104 citations

    2

    h-index

1–5