Multimodal Pattern Analysis

Multimodal Pattern Analysis is a systematic analytical approach that identifies, interprets, and models recurring structural or functional relationships across diverse modalities—such as linguistic, visual, auditory, and gestural data—within a multimodal corpus, distinguishing itself from unimodal or single-channel pattern detection by explicitly accounting for cross-modal interactions and integrative meaning-making.

43

Publications

1.4K

Citations

156

Authors

95

Institutions

Publications per year

2017–2026

26

Authors

156

  1. SC
    Shih‐Fu Chang

    Columbia University, United States

    2 publications · 28 citations

    2

    h-index

  2. PS
    Palaiahnakote Shivakumara

    University of Malaya, Malaysia

    1 publications · 13 citations

    1

    h-index

  3. KT
    Kok‐Sing Tang

    Curtin University, Australia

    1 publications · 26 citations

    1

    h-index

  4. BL
    Bin Liang

    Harbin Institute of Technology, China

    1 publications · 115 citations

    1

    h-index

  5. LH
    Luwei Hong

    Second Affiliated Hospital of Zhejiang University, China

    1 publications · 20 citations

    1

    h-index

1–5 of 156

Venues

  1. Neurocomputing

    1 publications · 41 citations

    3

    h-index

  2. Human Brain Mapping

    1 publications · 20 citations

    1

    h-index

  3. Research in Science Education

    1 publications · 26 citations

    1

    h-index

  4. Healthcare Analytics

    1 publications · 34 citations

    1

    h-index

  5. 1

    h-index

1–5