Feature Fusion

Feature Fusion is a methodological framework in multimedia retrieval that integrates complementary image features extracted from multiple sources or representations into a unified feature space to enhance discriminative power and retrieval accuracy.

6.5K

Publications

372K

Citations

22K

Authors

3.1K

Institutions

Publications per year

2017–2026

5K

Authors

22K

  1. LJ
    Licheng Jiao

    Xidian University, China

    30 publications · 1.8K citations

    22

    h-index

  2. WZ
    Wujie Zhou

    Zhejiang University of Science and Technology, China

    19 publications · 1.9K citations

    17

    h-index

  3. SC
    Shih‐Fu Chang

    Columbia University, United States

    19 publications · 1.6K citations

    17

    h-index

  4. QD
    Qian Du

    Mississippi State University, United States

    17 publications · 2.2K citations

    16

    h-index

  5. DT
    Dacheng Tao

    The University of Sydney, Australia

    18 publications · 2.5K citations

    16

    h-index

1–5 of 22K

Venues

  1. IEEE Transactions on Geoscience and Remote Sensing

    204 publications · 17.8K citations

    71

    h-index

  2. IEEE Access

    304 publications · 13.5K citations

    58

    h-index

  3. IEEE Transactions on Image Processing

    104 publications · 14.4K citations

    56

    h-index

  4. IEEE Transactions on Multimedia

    103 publications · 7K citations

    49

    h-index

  5. Sensors

    190 publications · 9.7K citations

    49

    h-index

1–5