Multimodal Recognition Fusion

Multimodal Recognition Fusion is a computational framework that integrates recognition outputs from multiple modality-specific models at a late stage to enhance overall decision accuracy by leveraging complementary information across modalities.

186

Publications

10.9K

Citations

755

Authors

308

Institutions

Publications per year

2017–2026

113

Authors

755

  1. SZ
    Stan Z. Li

    Chinese Academy of Sciences, China

    5 publications · 396 citations

    5

    h-index

  2. JW
    Jun Wan

    Chinese Academy of Sciences, China

    4 publications · 363 citations

    4

    h-index

  3. SP
    Simon Petitrenaud

    Le Mans Université, France

    3 publications · 56 citations

    3

    h-index

  4. GG
    Guodong Guo

    West Virginia University, United States

    3 publications · 278 citations

    3

    h-index

  5. XX
    Xiaona Xu

    Minzu University of China, China

    3 publications · 52 citations

    3

    h-index

1–5 of 755

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 256 citations

    9

    h-index

  2. IEEE Transactions on Multimedia

    6 publications · 271 citations

    6

    h-index

  3. Sensors

    5 publications · 258 citations

    5

    h-index

  4. 5

    h-index

  5. IEEE Access

    4 publications · 404 citations

    4

    h-index

1–5