The Combination and Application of CAD Data and Deep Learning Algorithms in Industrial Design

被引:0
|
作者
Wen Q. [1 ]
Liao H. [2 ]
机构
[1] Academy of Art, Jingchu University of Technology, Hubei, Jingmen
[2] College of Computer Science, Liaoning University, Liaoning, Shenyang
来源
Computer-Aided Design and Applications | 2024年 / 21卷 / S18期
关键词
Automation; CAD Data; Deep Learning; Industrial Design;
D O I
10.14733/cadaps.2024.S18.306-321
中图分类号
学科分类号
摘要
Industrial design is a complex process involving multiple disciplines and fields. With the increasing complexity of products and the diversification of market demand, design methods that rely on the experience and intuition of designers are no longer able to meet the needs. In order to promote the intelligence and automation of industrial design, this article proposes a DL-based CAD data processing method to optimize the product design stage. By introducing DL technology, this study successfully achieved automation and intelligence in the design stage, reducing the workload of designers. The convergence speed is compared to traditional algorithms when processing complex CAD data. In addition, the algorithm presented in this article performs better than traditional algorithms in terms of recall and accuracy, demonstrating the excellent ability of DL to handle large-scale and complex data structures. The DL-based CAD data processing method can effectively improve data processing performance and provide strong support for technological innovation in the field of industrial design. © 2024 U-turn Press LLC.
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页码:306 / 321
页数:15
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