Real-time Generative Systems

Real-Time Generative Systems is a computational framework within interactive generative systems that enables the continuous synthesis and adaptation of algorithmic art through immediate feedback loops, distinguished by its capacity to generate outputs instantaneously in response to dynamic inputs or environmental changes.

12

Publications

530

Citations

36

Authors

18

Institutions

Publications per year

2017–2026

8

Authors

36

  1. MG
    Mohsen Guizani

    Qatar University, Qatar

    2 publications · 89 citations

    2

    h-index

  2. VC
    Vinay Chamola

    Birla Institute of Technology and Science, Pilani, India

    2 publications · 89 citations

    2

    h-index

  3. FR
    F. Richard Yu

    Carleton University, Canada

    2 publications · 89 citations

    2

    h-index

  4. AH
    Amir Hussain

    Edinburgh Napier University, United Kingdom

    2 publications · 89 citations

    2

    h-index

  5. TK
    Tridib Kumar Das

    Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates

    2 publications · 89 citations

    2

    h-index

1–5 of 36

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 169 citations

    4

    h-index

  2. Digital Creativity

    1 publications · 23 citations

    1

    h-index

  3. Music Theory Online

    MTO · 1 publications · 86 citations

    1

    h-index

  4. Expert Systems with Applications

    1 publications · 19 citations

    1

    h-index

  5. Neural Computing and Applications

    1 publications · 55 citations

    1

    h-index

1–5