Visual Learning

Visual Learning is a computational framework that enables systems to acquire and refine knowledge through the processing and interpretation of visual stimuli, distinguishing itself by integrating perceptual representations with structured learning mechanisms to support tasks involving visual memory formation and recall.

1.5K

Publications

117.3K

Citations

4K

Authors

1.3K

Institutions

Publications per year

2017–2026

416

Authors

4K

  1. DG
    David Gaffan

    University of Oxford, United Kingdom

    20 publications · 2.2K citations

    19

    h-index

  2. TW
    Takeo Watanabe

    Brown University, United States

    16 publications · 684 citations

    15

    h-index

  3. AR
    Aaron R. Seitz

    University of California, Riverside, United States

    16 publications · 1.2K citations

    15

    h-index

  4. YS
    Yuka Sasaki

    Brown University, United States

    12 publications · 716 citations

    12

    h-index

  5. YJ
    Yuhong Jiang

    University of Minnesota, United States

    11 publications · 1.3K citations

    11

    h-index

1–5 of 4K

Venues

  1. Journal of Neuroscience

    30 publications · 3.4K citations

    25

    h-index

  2. arXiv (Cornell University)

    Repository · 43 publications · 10.9K citations

    20

    h-index

  3. Proceedings of the National Academy of Sciences

    PNAS · 23 publications · 4.2K citations

    20

    h-index

  4. Current Biology

    20 publications · 1.8K citations

    20

    h-index

  5. Journal of Vision

    32 publications · 1.2K citations

    19

    h-index

1–5