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.

中文翻译：

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基于无线网络多任务学习的绘画图像风格抄袭远程判断方法

由于作品的艺术性无法准确描述，可复制抄袭的认定就比较困难。数码影像作品可复制抄袭的认定，需要对艺术作品的艺术性进行深入研究。本文提出了一种基于无线网络多任务学习的绘画图像风格抄袭远程判断方法。根据这种新方法，基于多任务学习算法边缘采样去除绘画图像样本的不确定性。通过多任务分类核函数提取绘画图像的深层细节，消除图像中的大部分像素。当聚类密度大于判断阈值时，可以认为两幅图像具有空间一致性。也可据此判断两幅图像相似，即画作存在抄袭。实验结果表明，判别率始终接近100%，降低了对绘画图像抄袭的误判率，判别过程中各项指标最低，充分说明可以得到非常满意的判别结果。获得。