<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the rapid development of computer computing power, as an important method in the field of artificial intelligence, deep learning has amazing learning ability, especially in dealing with massive data, which makes deep learning in the fields of image recognition, image classification, natural language processing, data mining and unmanned driving, Has shown an extraordinary role. In previous studies, the style transfer algorithm has not developed well due to the poor computing power of Computer, the basic configuration of computer hardware can not meet the minimum requirements and the poor image effect after migration. However, with the development of computer hardware and the rapid change of GPU computing power, the style transfer network based on deep learning has become a hot issue in the study of style transfer in recent years. According to the research, although the traditional style transfer method can obtain the texture, color and other information of the style image, the model needs to be learned every time a new target image is generated, and the time cost during this period is very high. In this way, the trained model is not repeatable, and the generated image is often very random and can not get good results. Therefore, the emergence of style transfer methods based on deep learning solves the limitations of traditional style transfer methods. Style transfer methods based on deep learning are faster than traditional style transfer methods, and the generalization of the model is better. The style transfer algorithms of main neural networks are divided into two categories, Slow style transfer based on image iteration and fast style transfer based on model iteration. VGG network model can combine style image and content image, and greatly improve the style transfer efficiency of image.</p>
</abstract>

With the rapid development of computer computing power, as an important method in the field of artificial intelligence, deep learning has amazing learning ability, especially in dealing with massive data, which makes deep learning in the fields of image recognition, image classification, natural language processing, data mining and unmanned driving, Has shown an extraordinary role. In previous studies, the style transfer algorithm has not developed well due to the poor computing power of Computer, the basic configuration of computer hardware can not meet the minimum requirements and the poor image effect after migration. However, with the development of computer hardware and the rapid change of GPU computing power, the style transfer network based on deep learning has become a hot issue in the study of style transfer in recent years. According to the research, although the traditional style transfer method can obtain the texture, color and other information of the style image, the model needs to be learned every time a new target image is generated, and the time cost during this period is very high. In this way, the trained model is not repeatable, and the generated image is often very random and can not get good results. Therefore, the emergence of style transfer methods based on deep learning solves the limitations of traditional style transfer methods. Style transfer methods based on deep learning are faster than traditional style transfer methods, and the generalization of the model is better. The style transfer algorithms of main neural networks are divided into two categories, Slow style transfer based on image iteration and fast style transfer based on model iteration. VGG network model can combine style image and content image, and greatly improve the style transfer efficiency of image.

Style Transfer Based on VGG Network

School of Computer Science and Engineering

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Style Transfer Based on VGG Network"}

With the rapid development of computer computing power, as an important method in the field of artificial intelligence, deep learning has amazing learning...

Style Transfer Based on VGG Network

Data publikacji: 28 maj 2023

Zakres stron: 54 - 72

DOI: https://doi.org/10.2478/ijanmc-2022-0005

Słowa kluczowe
VGG Network, Neural Network, Style Transfer

© 2022 Zhe Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Style Transfer Based on VGG Network

Data publikacji: 28 maj 2023

Zakres stron: 54 - 72

DOI: https://doi.org/10.2478/ijanmc-2022-0005

Słowa kluczoweVGG Network, Neural Network, Style Transfer

© 2022 Zhe Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
VGG Network, Neural Network, Style Transfer