Evaluation and Design Method for Product Form Aesthetics Based on Deep Learning | |
Zhou, Aimin; Liu, Hongbin; Zhang, Shutao; Ouyang, Jinyan | |
刊名 | IEEE ACCESS |
2021 | |
卷号 | 9页码:108992-109003 |
关键词 | Licenses Convolution Predictive models Generative adversarial networks Training Task analysis Kernel Aesthetic evaluation aesthetic design product form deep learning |
ISSN号 | 2169-3536 |
DOI | 10.1109/ACCESS.2021.3101619 |
英文摘要 | Currently, evaluations of products from aesthetics are mostly carried out with knowledge expressions of aesthetic features as tools, achieving remarkable results. However, obtaining a large aesthetic feature vocabulary is a challenge because of the experience of researchers and the comprehension abilities of subjects. In addition, due to manual feature extraction, the sample sizes of experimental dataset are generally small, leading to results with poor generalization. To address this problem, a method of aesthetic evaluation and form design for products based on deep learning was proposed. First, a crawler tool was used to collect the front images of cars with corresponding appearance ratings, and a dataset was constructed with users' intuitive and simple ratings as the labels. A deep convolutional neural network (CNN) was designed, and a grading threshold was used as the classification basis. During the process of training the network, batch normalization and other methods were used to optimize the network, and good classification effects were achieved. Based on the above work, an adversarial neural network was used for the aesthetic design of a product form, a shape sketch of an automobile front face was generated, the proposed evaluation model was used to evaluate it, and the result obtained was excellent. These results show that the method used in this study can correctly evaluate product form aesthetics and then generate a design scheme with a high aesthetic level, thereby providing powerful technical support for the intelligent design of product forms. |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000683981900001 |
内容类型 | 期刊论文 |
源URL | [http://ir.lut.edu.cn/handle/2XXMBERH/148636] |
专题 | 设计艺术学院 |
作者单位 | Lanzhou Univ Technol, Sch Design Art, Lanzhou 730050, Peoples R China |
推荐引用方式 GB/T 7714 | Zhou, Aimin,Liu, Hongbin,Zhang, Shutao,et al. Evaluation and Design Method for Product Form Aesthetics Based on Deep Learning[J]. IEEE ACCESS,2021,9:108992-109003. |
APA | Zhou, Aimin,Liu, Hongbin,Zhang, Shutao,&Ouyang, Jinyan.(2021).Evaluation and Design Method for Product Form Aesthetics Based on Deep Learning.IEEE ACCESS,9,108992-109003. |
MLA | Zhou, Aimin,et al."Evaluation and Design Method for Product Form Aesthetics Based on Deep Learning".IEEE ACCESS 9(2021):108992-109003. |
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