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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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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 |
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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 |