| Title | CNN-Based Image Style Transfer and Its Applications |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Jin, N. |
| Conference Name | 2020 International Conference on Computing and Data Science (CDS) |
| Keywords | convolutional neural network, Data Science, Deep Learning, image style transfer, neural style transfer, Predictive Metrics, pubcrawl, Resiliency, Scalability |
| Abstract | Convolutional neural network is a variant of deep neural network. It is widely used to extract image features and used in image classification, image generation and style transfer. In the style transfer task, we can extract the content from one picture through the convolutional neural network, extract the style from another picture, and generate a new picture by the combination. In this paper, we show the general steps of image style transfer based on convolutional neural networks through a specific example, and discuss the future possible applications. |
| DOI | 10.1109/CDS49703.2020.00081 |
| Citation Key | jin_cnn-based_2020 |
CNN-Based Image Style Transfer and Its Applications