Hierarchical Image Classification

Hierarchical Image Classification is an image classification paradigm that organizes semantic categories into a hierarchical structure, distinguishing it from flat classification by exploiting parent-child relationships among classes to improve accuracy and model interpretability.

202

Publications

40.9K

Citations

648

Authors

280

Institutions

Publications per year

2017–2026

87

Authors

648

  1. JF
    Jianping Fan

    University of North Carolina at Charlotte, United States

    11 publications · 343 citations

    10

    h-index

  2. HL
    Hangzai Luo

    University of North Carolina at Charlotte, United States

    5 publications · 208 citations

    5

    h-index

  3. YZ
    Yu Zheng

    University of North Carolina at Charlotte, United States

    3 publications · 91 citations

    3

    h-index

  4. JP
    Jinye Peng

    Northwest University, China

    3 publications · 109 citations

    3

    h-index

  5. XY
    Xiaokang Yang

    Shanghai Jiao Tong University, China

    3 publications · 48 citations

    3

    h-index

1–5 of 648

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 761 citations

    11

    h-index

  2. IEEE Transactions on Image Processing

    7 publications · 1K citations

    7

    h-index

  3. Remote Sensing

    5 publications · 138 citations

    6

    h-index

  4. Pattern Recognition

    5 publications · 225 citations

    5

    h-index

  5. Multimedia Tools and Applications

    4 publications · 255 citations

    4

    h-index

1–5