Zhang Ailing
Shi Jia Zhuang University of Applied Technology, Shijiazhuang, Hebei, China.
PeerJ Comput Sci. 2024 Nov 26;10:e2492. doi: 10.7717/peerj-cs.2492. eCollection 2024.
In the era of continuous development of computer technology, the application of artificial intelligence (AI) and big data is becoming more and more extensive. With the help of powerful computer and network technology, the art of visual communication (VISCOM) has ushered in a new chapter of digitalization and intelligence. How vision can better perform interdisciplinary and interdisciplinary artistic expression between art and technology and how to use more novel technology, richer forms, and more appropriate ways to express art has become a new problem in visual art creation. This essay aims to investigate and apply VISCOM art through big data and AI methods. This essay proposed the STING algorithm for big data for multi-resolution information clustering in VISCOM art. In addition, the convolutional neural network (CNN) in AI technology was used to identify the conveyed objects or scenes to achieve the purpose of designing art with different characteristics for different scenes and groups of people. STING is a multi-resolution clustering technique for big data, with the advantage of efficient data processing. In the experimental part, this essay selected a variety of design contents in VISCOM art, including logo design, text design, scene design, packaging design and poster design. STING and CNN algorithms were used to cluster and AI-identify the design elements 16 of the design projects might contain. The results showed that the overall average clustering accuracy was above 82%, the accuracy of scene element recognition mainly was above 80%, and the accuracy of facial recognition was above 80%; this showed that this essay applied AI and big data to the design of VISCOM, and had a good effect on the clustering and identification of design elements. According to expert scores, these applications' reliability and practicality scores were above 70 points, with an average of about 80 points. Therefore, applying big data and AI to VISCOM in this essay is reliable and feasible.
在计算机技术不断发展的时代,人工智能(AI)和大数据的应用越来越广泛。借助强大的计算机和网络技术,视觉传达艺术(VISCOM)迎来了数字化和智能化的新篇章。视觉如何更好地在艺术与技术之间进行跨学科和多学科的艺术表达,以及如何运用更新颖的技术、更丰富的形式和更恰当的方式来表达艺术,已成为视觉艺术创作中的新问题。本文旨在通过大数据和AI方法对VISCOM艺术进行研究与应用。本文提出了用于VISCOM艺术中多分辨率信息聚类的大数据STING算法。此外,利用AI技术中的卷积神经网络(CNN)识别所传达的对象或场景,以实现针对不同场景和人群设计具有不同特征艺术作品的目的。STING是一种用于大数据的多分辨率聚类技术,具有高效的数据处理优势。在实验部分,本文选取了VISCOM艺术中的多种设计内容,包括标志设计、文本设计、场景设计、包装设计和海报设计。运用STING和CNN算法对16个设计项目可能包含的设计元素进行聚类和AI识别。结果表明,总体平均聚类准确率在82%以上,场景元素识别准确率主要在80%以上,人脸识别准确率在80%以上;这表明本文将AI和大数据应用于VISCOM设计中,对设计元素的聚类和识别有良好效果。根据专家评分,这些应用的可靠性和实用性得分均在70分以上,平均约为80分。因此,本文将大数据和AI应用于VISCOM是可靠且可行的。