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A Teaching Framework Based on Big Data of Students’ Learning Behaviors: A Case Study of Academic Performance Prediction Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Algorithm of Painting Style Transformation Based on Depth Neural Network

Authors : Haibing Li, Qian Jia

Published in: Frontier Computing

Publisher: Springer Nature Singapore

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Abstract

With the enrichment of material life, people’s demand for spiritual and cultural life is becoming stronger and stronger. As an important part of spiritual culture, artistic creation and entertainment consumption have also received more and more attention. The painting style conversion algorithm based on depth neural network is a technology that uses depth information to convert an image into another image. The algorithm is suitable for images with high contrast and sharp edges. It is also suitable for images with low contrast and blurred edges, but compared with other algorithms, it takes more time to complete this process. The painting style conversion algorithm based on depth neural network is a technology that uses depth information to convert an image into another image. The algorithm is suitable for images with high contrast and sharp edges. It is also suitable for images with low contrast and blurred edges. This algorithm is used to convert the sample image into a new image of Xin’an painting style.

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Metadata
Title
Algorithm of Painting Style Transformation Based on Depth Neural Network
Authors
Haibing Li
Qian Jia
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Frontier Computing

Print ISBN: 978-981-9914-27-2

Electronic ISBN: 978-981-9914-28-9

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-99-1428-9_221