Cargando…

Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication

People are increasingly enthusiastic about pursuing spiritual life as economic and social development continues. Consequently, public cultural content has emerged as a pivotal instrument for promoting international soft power across diverse nations and regions. In today’s era of advanced artificial...

Descripción completa

Detalles Bibliográficos
Autores principales: Gong, Xiang, Fang, Jingyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280649/
https://www.ncbi.nlm.nih.gov/pubmed/37346514
http://dx.doi.org/10.7717/peerj-cs.1399
_version_ 1785060844074172416
author Gong, Xiang
Fang, Jingyi
author_facet Gong, Xiang
Fang, Jingyi
author_sort Gong, Xiang
collection PubMed
description People are increasingly enthusiastic about pursuing spiritual life as economic and social development continues. Consequently, public cultural content has emerged as a pivotal instrument for promoting international soft power across diverse nations and regions. In today’s era of advanced artificial intelligence, cultural sign design optimization has become achievable through its deployment. This article establishes an automatic layout optimization framework, specifically tailored to meet the visual communication requirements of public cultural signage. Our framework employs Faster-R-CNN for detecting and extracting key elements of the poster, yielding an impressive average detection accuracy of 94.6%. Subsequently, we use the three-division method in design to optimize the layout, ensuring that cultural logo design conforms to visual communication principles. Our framework produced an average cultural logo satisfaction rating exceeding 70% in actual tests, providing novel insights for cultural sign design within the artificial intelligence context and significantly enhancing the efficacy of visual communication conveyed through such signage.
format Online
Article
Text
id pubmed-10280649
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher PeerJ Inc.
record_format MEDLINE/PubMed
spelling pubmed-102806492023-06-21 Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication Gong, Xiang Fang, Jingyi PeerJ Comput Sci Artificial Intelligence People are increasingly enthusiastic about pursuing spiritual life as economic and social development continues. Consequently, public cultural content has emerged as a pivotal instrument for promoting international soft power across diverse nations and regions. In today’s era of advanced artificial intelligence, cultural sign design optimization has become achievable through its deployment. This article establishes an automatic layout optimization framework, specifically tailored to meet the visual communication requirements of public cultural signage. Our framework employs Faster-R-CNN for detecting and extracting key elements of the poster, yielding an impressive average detection accuracy of 94.6%. Subsequently, we use the three-division method in design to optimize the layout, ensuring that cultural logo design conforms to visual communication principles. Our framework produced an average cultural logo satisfaction rating exceeding 70% in actual tests, providing novel insights for cultural sign design within the artificial intelligence context and significantly enhancing the efficacy of visual communication conveyed through such signage. PeerJ Inc. 2023-06-13 /pmc/articles/PMC10280649/ /pubmed/37346514 http://dx.doi.org/10.7717/peerj-cs.1399 Text en ©2023 Gong and Fang https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Artificial Intelligence
Gong, Xiang
Fang, Jingyi
Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication
title Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication
title_full Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication
title_fullStr Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication
title_full_unstemmed Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication
title_short Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication
title_sort design of public cultural sign based on faster-r-cnn and its application in urban visual communication
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280649/
https://www.ncbi.nlm.nih.gov/pubmed/37346514
http://dx.doi.org/10.7717/peerj-cs.1399
work_keys_str_mv AT gongxiang designofpublicculturalsignbasedonfasterrcnnanditsapplicationinurbanvisualcommunication
AT fangjingyi designofpublicculturalsignbasedonfasterrcnnanditsapplicationinurbanvisualcommunication