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The Application of RBF Neural Network Model Based on Deep Learning for Flower Pattern Design in Art Teaching.

Authors :
Xiao, Lijun
Luo, Yan
Source :
Computational Intelligence & Neuroscience; 6/13/2022, p1-9, 9p
Publication Year :
2022

Abstract

The rapid growth of artificial intelligence technology has been deployed in art teaching and learning. Radial basis function (RBF) networks have a completely different design compared to most neural network architectures. Most neural networks consist of multiple layers that can introduce nonlinearity by repetitive application of nonlinear activation functions. In this research, people will study the application of the RBF neural network model based on deep learning in flower pattern design in art teaching. The image classification process is finding and labeling groups of pixels or vectors inside an image based on rules. Deep learning is a type of machine learning that uses artificial neural networks to replicate the structure and function of the human brain. The proposed model uses the RBF neural network-based deep learning model in flower pattern design in art teaching and provides efficient results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16875265
Database :
Complementary Index
Journal :
Computational Intelligence & Neuroscience
Publication Type :
Academic Journal
Accession number :
157408900
Full Text :
https://doi.org/10.1155/2022/4206857