1. Feature extraction method of 3D art creation based on deep learning
- Author
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Kaiqing Chen and Xiaoqin Huang
- Subjects
0209 industrial biotechnology ,Process (engineering) ,business.industry ,Computer science ,Deep learning ,Feature extraction ,Computational intelligence ,02 engineering and technology ,Machine learning ,computer.software_genre ,Theoretical Computer Science ,020901 industrial engineering & automation ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Social media ,Geometry and Topology ,Artificial intelligence ,Evolution strategy ,business ,computer ,Software - Abstract
In order to study the method of feature extraction of 3D art design model based on deep learning, in this study, a network community media communication research on 3D art creation based on deep learning and evolution strategy was proposed. The research results showed that the two feature extraction methods were reliable and robust. Based on the evolutionary strategy, the evolution matrix function was used to extract the characteristics of people’s preferences. The experimental results showed that the process is feasible. It can be concluded that the method based on the method of deep learning and interactive evolution strategy, the feasibility of social media communication research of 3D art creation network based on deep learning and evolution strategy was verified by the combination of scientific creation and artistic creation by sacrificing time expenditure.
- Published
- 2019
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