Image-based Misinformation Detection

Image-Based Misinformation Detection is a computational method that identifies false or misleading information propagated through digital images by analyzing visual content, metadata, and contextual cues to distinguish deceptive or manipulated imagery from authentic sources.

64

Publications

3.6K

Citations

242

Authors

107

Institutions

Publications per year

2017–2026

58

Authors

242

  1. JC
    Juan Cao

    Chinese Academy of Sciences, China

    4 publications · 826 citations

    4

    h-index

  2. KA
    Kimberley A. Wade

    University of Warwick, United Kingdom

    2 publications · 183 citations

    2

    h-index

  3. JL
    Jintao Li

    Chinese Academy of Sciences, China

    2 publications · 330 citations

    2

    h-index

  4. PQ
    Peng Qi

    Stanford University, United States

    2 publications · 330 citations

    2

    h-index

  5. RZ
    Richard Zhang

    Adobe Systems (United States), United States

    2 publications · 160 citations

    2

    h-index

1–5 of 242

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 141 citations

    4

    h-index

  2. Cognitive Research Principles and Implications

    2 publications · 183 citations

    2

    h-index

  3. Frontiers in Communication

    1 publications · 51 citations

    1

    h-index

  4. Pattern Recognition Letters

    1 publications · 10 citations

    1

    h-index

  5. Applied Intelligence

    1 publications · 38 citations

    1

    h-index

1–5