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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2023-06-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-1399.pdf |
| _version_ | 1797803318471294976 |
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| author | Xiang Gong Jingyi Fang |
| author_facet | Xiang Gong Jingyi Fang |
| author_sort | Xiang Gong |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-13T05:19:01Z |
| format | Article |
| id | doaj.art-48ec977f5f454a1091e9cba482b29134 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-03-13T05:19:01Z |
| publishDate | 2023-06-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-48ec977f5f454a1091e9cba482b291342023-06-15T15:05:11ZengPeerJ Inc.PeerJ Computer Science2376-59922023-06-019e139910.7717/peerj-cs.1399Design of public cultural sign based on Faster-R-CNN and its application in urban visual communicationXiang Gong0Jingyi Fang1Department of Arts Design, Visual Communication Design Major, Dankook University, Yongin-si, KoreaDepartment of Arts Design, Visual Communication Design Major, Dankook University, Yongin-si, KoreaPeople 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.https://peerj.com/articles/cs-1399.pdfVisual CommunicationPublic Cultural SignsDeep learningObject detection |
| spellingShingle | Xiang Gong Jingyi Fang Design of public cultural sign based on Faster-R-CNN and its application in urban visual communication PeerJ Computer Science Visual Communication Public Cultural Signs Deep learning Object detection |
| 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 | Visual Communication Public Cultural Signs Deep learning Object detection |
| url | https://peerj.com/articles/cs-1399.pdf |
| work_keys_str_mv | AT xianggong designofpublicculturalsignbasedonfasterrcnnanditsapplicationinurbanvisualcommunication AT jingyifang designofpublicculturalsignbasedonfasterrcnnanditsapplicationinurbanvisualcommunication |