Recursive Pattern Generation

Recursive Pattern Generation is a procedural image generation method that iteratively applies rule-based transformations to a primitive graphical element, where each output serves as input for subsequent iterations, thereby producing self-similar or nested visual structures through recursive feedback.

13

Publications

687

Citations

26

Authors

17

Institutions

Publications per year

2017–2026

2

Authors

26

  1. DK
    David Kurlander

    Columbia University, United States

    2 publications · 116 citations

    2

    h-index

  2. EA
    Eric A. Bier

    Palo Alto Research Center, United States

    2 publications · 116 citations

    2

    h-index

  3. MT
    M.R. Titchener

    University of Auckland, New Zealand

    1 publications · 29 citations

    1

    h-index

  4. KJ
    Karl Josef Fuchs

    Technical University of Munich, Germany

    1 publications · 84 citations

    1

    h-index

  5. JT
    Jerzy Tyszer

    Poznań University of Technology, Poland

    1 publications · 22 citations

    1

    h-index

1–5 of 26

Venues

  1. Science Advances

    2 publications · 116 citations

    2

    h-index

  2. IEEE Transactions on Computers

    1 publications · 22 citations

    1

    h-index

  3. 1

    h-index

  4. Pattern Recognition Letters

    1 publications · 30 citations

    1

    h-index

  5. Environment and Planning B Planning and Design

    1 publications · 198 citations

    1

    h-index

1–5