Grammar-based Shape Classification

Grammar-Based Shape Classification is a computational framework within the field of shape grammars that classifies two-dimensional shapes by identifying and applying rule-based generative processes derived from formal grammars, distinguishing it from statistical or feature-based classification methods through its reliance on syntactic, rule-driven shape generation and transformation.

4

Publications

218

Citations

10

Authors

7

Institutions

Publications per year

2017–2026

0

Authors

10

  1. NK
    Noriko Kando

    National Institute of Informatics, Japan

    1 publications · 13 citations

    1

    h-index

  2. BB
    Benjamin B. Kimia

    Brown University, United States

    1 publications · 161 citations

    1

    h-index

  3. AE
    A. Einifar

    École Normale Supérieure - PSL, France

    1 publications · 13 citations

    1

    h-index

  4. LF
    L. F. Pau

    Technical University of Denmark, Denmark

    1 publications · 11 citations

    1

    h-index

  5. PL
    Pierre Lebigre

    National Institute of Informatics, Japan

    1 publications · 13 citations

    1

    h-index

1–5 of 10

Venues

  1. Machine Vision and Applications

    1 publications · 11 citations

    1

    h-index

  2. 1

    h-index

  3. Journal of Cultural Heritage

    1 publications · 13 citations

    1

    h-index

  4. Language

    1 publications · 56 citations

1–4