This work is licensed under the Creative Commons Attribution 4.0 International License.
Jing, Y., Yang, Y., Feng, Z., Ye, J., Yu, Y., & Song, M. (2019). Neural style transfer: A review. IEEE transactions on visualization and computer graphics, 26(11), 3365-3385.Search in Google Scholar
Ghiasi, G., Lee, H., Kudlur, M., Dumoulin, V., & Shlens, J. (2017). Exploring the structure of a real-time, arbitrary neural artistic stylization network. In Procedings of the British Machine Vision Conference 2017. British Machine Vision Association.Search in Google Scholar
Zhang, W. N., Zhu, Q., Wang, Y., Zhao, Y., & Liu, T. (2019). Neural personalized response generation as domain adaptation. World Wide Web, 22, 1427-1446.Search in Google Scholar
Shen, Y., & Yu, F. (2021). The influence of artificial intelligence on art design in the digital age. Scientific programming, 2021(1), 4838957.Search in Google Scholar
Zeng, L., & Dong, X. (2021). Artistic style conversion based on 5g virtual reality and virtual reality visual space. Mobile Information Systems.Search in Google Scholar
Engineering, M. P. I. (2023). Retracted: design of artistic creation style extraction model based on color feature data. Mathematical Problems in Engineering.Search in Google Scholar
Messina, P., Dominguez, V., Parra, D., Trattner, C., & Soto, A. (2019). Content-based artwork recommendation: integrating painting metadata with neural and manually-engineered visual features. User Modeling and User-Adapted Interaction, 29(2), 251-290.Search in Google Scholar
Trichopoulos, G., Aliprantis, J., Konstantakis, M., & Caridakis, G. (2018). ARTISTS: A virtual Reality culTural experIence perSonalized arTworks System: The “Children Concert” painting case study. In Proceedings of the International Conference on Digital Culture & AudioVisual Challenges (DCAC-2018).Search in Google Scholar
Chao, H. (2020). The fractal artistic design based on interactive genetic algorithm. Computer-Aided Design and Applications, 17(S2), 35-45.Search in Google Scholar
Kai Yang. (2023). Application of Depth Learning Algorithm in Automatic Processing and Analysis of Sports Images. Computer Systems Science and Engineering(1),317-332.Search in Google Scholar
Liyong Chen & Xiuye Yin. (2021). Recognition Method of Abnormal Behavior of Marine Fish Swarm Based on In-Depth Learning Network Model. Journal of Web Engineering(3),575-596.Search in Google Scholar
Xu Haowei, Xing Junhui, Yang Boxue & Liu Chuang. (2024). Auto-Detection Method Using Convolution Neural Network for Bottom-Simulating Reflectors. Journal of Ocean University of China(3),683-694.Search in Google Scholar
Mohamed Amine Zayene, Hend Basly & Fatma Ezahra Sayadi. (2024). Multi-View Separable Residual convolution neural Network for detecting Alzheimer’s disease progression. Biomedical Signal Processing and Control(PB),106375-.Search in Google Scholar