Cross-modal Object Recognition

Cross-Modal Object Recognition is a computational framework within object recognition that integrates and aligns visual and non-visual sensory inputs—such as auditory, tactile, or linguistic modalities—to achieve invariant object representation and recognition across different perceptual channels.

74

Publications

3.9K

Citations

188

Authors

84

Institutions

Publications per year

2017–2026

25

Authors

188

  1. BD
    Boyer D. Winters

    University of Guelph, Canada

    4 publications · 239 citations

    4

    h-index

  2. FN
    Fiona N. Newell

    Trinity College Dublin, Ireland

    4 publications · 179 citations

    4

    h-index

  3. HL
    Huaping Liu

    Tsinghua University, China

    4 publications · 103 citations

    4

    h-index

  4. FS
    Fuchun Sun

    Tsinghua University, China

    4 publications · 103 citations

    4

    h-index

  5. DL
    Derek L. Jacklin

    University of Guelph, Canada

    3 publications · 120 citations

    3

    h-index

1–5 of 188

Venues

  1. Journal of Neuroscience

    3 publications · 286 citations

    3

    h-index

  2. Developmental Psychology

    3 publications · 77 citations

    3

    h-index

  3. Child Development

    3 publications · 381 citations

    3

    h-index

  4. PLoS ONE

    3 publications · 188 citations

    3

    h-index

  5. 3

    h-index

1–5