The application of big data technology in the art of visual communication design with information technology
Based on big data technology, this paper firstly proposes that visual image generation design based on the improved adversarial generative network becomes one of the ideas to solve the current dilemma of visual communication design, which is not only a convenient, creative means but also changes the...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.00370 |
| _version_ | 1797340804549705728 |
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| author | Tao Peitian Wang Wenyan |
| author_facet | Tao Peitian Wang Wenyan |
| author_sort | Tao Peitian |
| collection | DOAJ |
| description | Based on big data technology, this paper firstly proposes that visual image generation design based on the improved adversarial generative network becomes one of the ideas to solve the current dilemma of visual communication design, which is not only a convenient, creative means but also changes the traditional way of visual communication design. Secondly, in the extension of visual image samples, in addition to using some operations such as rotation, translation and scale transformation of visual images, an improved DCGAN adversarial generative network algorithm is also used. The improved DCGAN network is then used to augment the number of visual images while maintaining the quality of visual image generation. Finally, intelligent generation models based on visual communication design processes and thinking are investigated, focusing on intelligent data sets and retrieval, image generation techniques, and intelligent solution recommendations. The results show that DCGAN has a lower value of IS = 1.5, FID = 249.39, IS and a higher value of FID, indicating that it generates better quality visual images and greatly improves the efficiency and accuracy of visual communication design. This study can extract effective information and generate visual images more accurately and efficiently, and provide technical support for visual communication designers. |
| first_indexed | 2024-03-08T10:08:40Z |
| format | Article |
| id | doaj.art-4ef67af169c4402b8575b353ff0a5bd6 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:08:40Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-4ef67af169c4402b8575b353ff0a5bd62024-01-29T08:52:31ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.00370The application of big data technology in the art of visual communication design with information technologyTao Peitian0Wang Wenyan11Nanchang Institute of Science & Technology, Nanchang, Jiangxi, 330108, China.1Nanchang Institute of Science & Technology, Nanchang, Jiangxi, 330108, China.Based on big data technology, this paper firstly proposes that visual image generation design based on the improved adversarial generative network becomes one of the ideas to solve the current dilemma of visual communication design, which is not only a convenient, creative means but also changes the traditional way of visual communication design. Secondly, in the extension of visual image samples, in addition to using some operations such as rotation, translation and scale transformation of visual images, an improved DCGAN adversarial generative network algorithm is also used. The improved DCGAN network is then used to augment the number of visual images while maintaining the quality of visual image generation. Finally, intelligent generation models based on visual communication design processes and thinking are investigated, focusing on intelligent data sets and retrieval, image generation techniques, and intelligent solution recommendations. The results show that DCGAN has a lower value of IS = 1.5, FID = 249.39, IS and a higher value of FID, indicating that it generates better quality visual images and greatly improves the efficiency and accuracy of visual communication design. This study can extract effective information and generate visual images more accurately and efficiently, and provide technical support for visual communication designers.https://doi.org/10.2478/amns.2023.2.00370big data technologyadversarial generative networksvisual communication designis valuefid values65d17 |
| spellingShingle | Tao Peitian Wang Wenyan The application of big data technology in the art of visual communication design with information technology Applied Mathematics and Nonlinear Sciences big data technology adversarial generative networks visual communication design is value fid values 65d17 |
| title | The application of big data technology in the art of visual communication design with information technology |
| title_full | The application of big data technology in the art of visual communication design with information technology |
| title_fullStr | The application of big data technology in the art of visual communication design with information technology |
| title_full_unstemmed | The application of big data technology in the art of visual communication design with information technology |
| title_short | The application of big data technology in the art of visual communication design with information technology |
| title_sort | application of big data technology in the art of visual communication design with information technology |
| topic | big data technology adversarial generative networks visual communication design is value fid values 65d17 |
| url | https://doi.org/10.2478/amns.2023.2.00370 |
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