Labels

Labels is a visual annotation technique that belongs to the class of textual aids in visualization, differentiating itself by explicitly identifying specific data elements, features, or regions within a visual representation to enhance interpretability and direct viewer attention.

8.4K

Publications

644.3K

Citations

24.7K

Authors

4.4K

Institutions

Publications per year

2017–2026

4.2K

Authors

24.7K

  1. ZZ
    Zhi‐Hua Zhou

    Nanjing University, China

    32 publications · 2.1K citations

    26

    h-index

  2. YY
    Yi Yang

    University of Technology Sydney, Australia

    26 publications · 3.6K citations

    23

    h-index

  3. XG
    Xin Geng

    Southeast University, China

    31 publications · 2.9K citations

    23

    h-index

  4. GN
    Gang Niu

    Xi'an Jiaotong University, China

    27 publications · 3.1K citations

    22

    h-index

  5. BH
    Bo Han

    Hong Kong Baptist University, Hong Kong SAR China

    29 publications · 3.2K citations

    22

    h-index

1–5 of 24.7K

Venues

  1. arXiv (Cornell University)

    Repository · 642 publications · 56.9K citations

    89

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 166 publications · 12.7K citations

    55

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 100 publications · 18.8K citations

    52

    h-index

  4. IEEE Transactions on Image Processing

    77 publications · 6.6K citations

    43

    h-index

  5. 38

    h-index

1–5