Calligraphic Generation

Calligraphic Generation is a generative method in the field of computational art and design that produces visual forms through algorithmically simulated handwriting or stroke-based gestures, distinguished by its emphasis on expressive, time-ordered, and kinesthetically informed mark-making as a core generative principle.

54

Publications

1.6K

Citations

159

Authors

66

Institutions

Publications per year

2017–2026

15

Authors

159

  1. CZ
    Changle Zhou

    Xiamen University, China

    7 publications · 199 citations

    7

    h-index

  2. YP
    Yunhe Pan

    Zhejiang University, China

    7 publications · 137 citations

    7

    h-index

  3. CS
    Changjing Shang

    Aberystwyth University, United Kingdom

    6 publications · 176 citations

    6

    h-index

  4. LY
    Longzhi Yang

    Northumbria University, United Kingdom

    6 publications · 176 citations

    6

    h-index

  5. FC
    Fei Chao

    Xiamen University, China

    5 publications · 148 citations

    5

    h-index

1–5 of 159

Venues

  1. IEEE Intelligent Systems

    3 publications · 71 citations

    3

    h-index

  2. Knowledge-Based Systems

    2 publications · 57 citations

    2

    h-index

  3. Goldsmiths (University of London)

    Repository · 2 publications · 26 citations

    2

    h-index

  4. Computer Graphics Forum

    2 publications · 31 citations

    2

    h-index

  5. Neurocomputing

    2 publications · 48 citations

    2

    h-index

1–5