Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask Learning

Since the artistry of the work cannot be accurately described, the identification of reproducible plagiarism is more difficult. The identification of reproducible plagiarism of digital image works requires in-depth research on the artistry of artistic works. In this paper, a remote judgment method f...

Full description

Bibliographic Details
Main Author: Zhijun Wang
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2021/1345974
id doaj-87cc150f9e79438e9c35d408b72ef0ce
record_format Article
spelling doaj-87cc150f9e79438e9c35d408b72ef0ce2021-09-20T00:29:33ZengHindawi-WileyWireless Communications and Mobile Computing1530-86772021-01-01202110.1155/2021/1345974Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask LearningZhijun Wang0Academy of Fine ArtsSince the artistry of the work cannot be accurately described, the identification of reproducible plagiarism is more difficult. The identification of reproducible plagiarism of digital image works requires in-depth research on the artistry of artistic works. In this paper, a remote judgment method for plagiarism of painting image style based on wireless network multitask learning is proposed. According to this new method, the uncertainty of painting image samples is removed based on multitask learning algorithm edge sampling. The deep-level details of the painting image are extracted through the multitask classification kernel function, and most of the pixels in the image are eliminated. When the clustering density is greater than the judgment threshold, it can be considered that the two images have spatial consistency. It can also be judged based on this that the two images are similar, that is, there is plagiarism in the painting. The experimental results show that the discrimination rate is always close to 100%, the misjudgment rate of plagiarism of painting images has been reduced, and the various indicators in the discrimination process are the lowest, which fully shows that a very satisfactory discrimination result can be obtained.http://dx.doi.org/10.1155/2021/1345974
collection DOAJ
language English
format Article
sources DOAJ
author Zhijun Wang
spellingShingle Zhijun Wang
Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask Learning
Wireless Communications and Mobile Computing
author_facet Zhijun Wang
author_sort Zhijun Wang
title Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask Learning
title_short Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask Learning
title_full Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask Learning
title_fullStr Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask Learning
title_full_unstemmed Remote Judgment Method of Painting Image Style Plagiarism Based on Wireless Network Multitask Learning
title_sort remote judgment method of painting image style plagiarism based on wireless network multitask learning
publisher Hindawi-Wiley
series Wireless Communications and Mobile Computing
issn 1530-8677
publishDate 2021-01-01
description Since the artistry of the work cannot be accurately described, the identification of reproducible plagiarism is more difficult. The identification of reproducible plagiarism of digital image works requires in-depth research on the artistry of artistic works. In this paper, a remote judgment method for plagiarism of painting image style based on wireless network multitask learning is proposed. According to this new method, the uncertainty of painting image samples is removed based on multitask learning algorithm edge sampling. The deep-level details of the painting image are extracted through the multitask classification kernel function, and most of the pixels in the image are eliminated. When the clustering density is greater than the judgment threshold, it can be considered that the two images have spatial consistency. It can also be judged based on this that the two images are similar, that is, there is plagiarism in the painting. The experimental results show that the discrimination rate is always close to 100%, the misjudgment rate of plagiarism of painting images has been reduced, and the various indicators in the discrimination process are the lowest, which fully shows that a very satisfactory discrimination result can be obtained.
url http://dx.doi.org/10.1155/2021/1345974
work_keys_str_mv AT zhijunwang remotejudgmentmethodofpaintingimagestyleplagiarismbasedonwirelessnetworkmultitasklearning
_version_ 1717375156032110592