Computer Aided Art Modeling Design Method Based on Improved Genetic Algorithm

被引：0
作者：
Wang X. [1 ]
Lei Z. [1 ]
机构：
[1] College of Art and Design, Henan Economy and Trade Vocational College, Henan, Zhengzhou
来源：
Comput.-Aided Des. Appl. | 2024年 / S1卷 / 74-87期
关键词：
Art Modeling Design; CAD; Deep Learning; Feature Extraction;
D O I：
10.14733/cadaps.2024.S1.74-87
中图分类号：
学科分类号：
摘要：
Combining with the needs of art design, the growth of art design CAD system is not only conducive to improving the efficiency of art design, but also to further improve the level of art design. Art CAD creation based on CAD systems plays an important role in neural network systems. Compared with traditional design methods, it has more efficiency advantages in system design efficiency. In the traditional process of artistic expression analysis, this article constructs a convolutional network feature extraction optimization model for computer art model design. This model optimizes some of the shortcomings of traditional methods. Corresponding weights are set according to the different obtained feature information in multiple convolution layers of the network, and a label set with multi-category labels is created, which can be classified many times in one transmission, thus expanding the differences between fine-grained images. © 2024, CAD Solutions, LLC. All rights reserved.
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页码：74 / 87
页数：13
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共 15 条
  • [1] Bhatt P.-M., Malhan R.-K., Rajendran P., Shah B.-C., Thakar S., Yoon Y.-J., Gupta S.- K., Image-based surface defect detection using deep learning: A review, Journal of Computing and Information Science in Engineering, 21, 4, pp. 1-15, (2021)
  • [2] Deng J., Chen X., Research on Artificial Intelligence Interaction in Computer-Aided Arts and Crafts, Mobile Information Systems, 2021, 10, pp. 1-14, (2021)
  • [3] Ghosh S., Das N., Das I., Maulik U., Understanding deep learning techniques for image segmentation, ACM Computing Surveys (CSUR), 52, 4, pp. 1-35, (2019)
  • [4] Guo S., Li X., Computer Aided Art Design and Production Based on Video Stream, Computer-Aided Design and Applications, 18, pp. 70-81, (2020)
  • [5] Guo S., Wang B., Application of Computer Aided Modeling Design in the Expression Techniques of Sculpture Art Space, Computer-Aided Design and Applications, 19, 3, (2021)
  • [6] He C., Sun B., Application of artificial intelligence technology in computer aided art teaching, Computer-Aided Design and Applications, 18, pp. 118-129, (2021)
  • [7] Hu L., Application of AutoCAD’s 3D Modeling Function in Industrial Modeling Design, Computer-Aided Design and Applications, 18, 1, pp. 33-42, (2020)
  • [8] Jang J., Shin M., Lim S., Park J., Kim J., Paik J., Intelligent image-based railway inspection system using deep learning-based object detection and weber contrast-based image comparison, Sensors, 19, 21, (2019)
  • [9] Jing Y., Song Y., Application of 3D Reality Technology Combined with CAD in Animation Modeling Design, Computer-Aided Design and Applications, 18, 3, pp. 164-175, (2020)
  • [10] Lu X., Chen Y., Li X., Discrete deep hashing with ranking optimization for image retrieval, IEEE Transactions on Neural Networks and Learning Systems, 31, 6, pp. 2052-2063, (2019)
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