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Poster Page Layout Design Method Based on Visual Communication Technology

Author

Listed:
  • Qiaoran Li

    (Shangqiu University, China)

  • Shanshan Xu

    (Wuhan Technical College of Communications, China)

Abstract

This study explored how advanced artificial intelligence technologies, particularly convolutional neural networks (CNNs), can be applied to visual communication design, especially for automated poster layout generation. The study innovatively combined CNN technology with design practices, proposing an object detection model to identify and locate poster elements. This approach improved classification and localization accuracy in complex scenarios, laying the foundation for more efficient and precise automated design tools. The research covered experiment design, CNN application, layout model construction, and optimization processes. Aesthetic principles like the golden ratio and rule of thirds were applied to enhance visual appeal. By integrating these strategies, the study achieved a transition from design logic to computational logic, generating diverse design solutions. It offers new perspectives for artificial-intelligence-assisted visual communication design.

Suggested Citation

  • Qiaoran Li & Shanshan Xu, 2025. "Poster Page Layout Design Method Based on Visual Communication Technology," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global Scientific Publishing, vol. 19(1), pages 1-19, January.
    • Handle: RePEc:igg:jcini0:v:19:y:2025:i:1:p:1-19
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    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJCINI.394821
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    References listed on IDEAS

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    1. Jun Li & Jiye Li & Yazhi Yang & Zhaoxu Ren & Gengxin Sun, 2021. "Design of Higher Education System Based on Artificial Intelligence Technology," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-11, December.
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