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Soft Computing

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20.09.2019 | Focus

Feature extraction method of 3D art creation based on deep learning

verfasst von: Kaiqing Chen, Xiaoqin Huang

Erschienen in: Soft Computing | Ausgabe 11/2020

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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.

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Titel: Feature extraction method of 3D art creation based on deep learning
verfasst von: Kaiqing Chen
Xiaoqin Huang
Publikationsdatum: 20.09.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 11/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-04353-0

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