Machine Learning Model to Evaluate the Appropriateness of Layout for Automatic Generation of Graphic Design Works

Kohei Ishiyama, Taketoshi Ushiama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Generative networks (GANs) are commonly used for image generation to generate images with noise as input to the trained generator. However, it is difficult to generate appropriate graphic designs with GANs when the user specifies the material images and text to be used as input, as in the case of graphic design. In this study, we focus on the graphic design layout and propose a method for automatically generating graphic designs using adversarial GANs. We trained the generator and discriminator using GANs by converting the training data of graphic designs into images that represent their visual importance. The trained discriminators were then used to evaluate the automatically generated layouts using specified materials. The results of experiments with subjective evaluations using subjects indicates that the proposed method was effective.

Original languageEnglish
Title of host publicationProceedings of the 2023 17th International Conference on Ubiquitous Information Management and Communication, IMCOM 2023
EditorsSukhan Lee, Hyunseung Choo, Roslan Ismail
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665453486
DOIs
Publication statusPublished - 2023
Event17th International Conference on Ubiquitous Information Management and Communication, IMCOM 2023 - Seoul, Korea, Republic of
Duration: Jan 3 2023Jan 5 2023

Publication series

NameProceedings of the 2023 17th International Conference on Ubiquitous Information Management and Communication, IMCOM 2023

Conference

Conference17th International Conference on Ubiquitous Information Management and Communication, IMCOM 2023
Country/TerritoryKorea, Republic of
CitySeoul
Period1/3/231/5/23

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Numerical Analysis
  • Health Informatics
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

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