Image Style Transfer Based on VGG Neural Network Model | |
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Author | |
Abstract |
Neural Style Transfer - Image style transfer is an important research content related to image processing in computer vision. Compared with traditional artificial computing methods, deep learning-based convolutional neural networks in the field of machine learning have powerful advantages. This new method has high computational efficiency and a good style transfer effect. To further improve the quality and efficiency of image style transfer, the pre-trained VGG-16 neural network model and VGG-19 neural network model are used to achieve image style transfer, and the transferred images generated by the two neural networks are compared. The research results show that the use of the VGG-16 convolutional neural network to achieve image style transfer is better and more efficient. |
Year of Publication |
2022
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Date Published |
aug
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Publisher |
IEEE
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Conference Location |
Dalian, China
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ISBN Number |
978-1-66548-090-1
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URL |
https://ieeexplore.ieee.org/document/9918891/
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DOI |
10.1109/AEECA55500.2022.9918891
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Google Scholar | BibTeX | DOI |