IkebanaGAN: New GANs Technique for Digital Ikebana Art-Reference-Cited by-同舟云学术

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IkebanaGAN: New GANs Technique for Digital Ikebana Art

Published:2021 Issue: Volume: Page:88-99
ISSN:0302-9743
Container-title:Culture and Computing. Interactive Cultural Heritage and Arts
language:
Short-container-title:

Author:

Hung Mai Cong,Trang Mai Xuan,Tosa Naoko,Nakatsu Ryohei

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-77411-0_7

Reference10 articles.

1. Gultepe, E., Conturo, T.E., Makrehchi, M.: Predicting and grouping digitized paintings by style using unsupervised feature learning. J Cult. Herit. 31, 13–23 (2018). https://doi.org/10.1016/j.culher.2017.11.008. Epub 2017 Dec 20. PMID: 30034259; PMCID: PMC6051702

2. Lecture Notes in Computer Science;CH Mai,2020

3. Creswell, A., et al.: Generative adversarial networks: an overview. IEEE Sig. Process. Mag. 35(1), 53–65 (2018)

4. Zhu, J., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2242–2251 (2017)

5. Lecture Notes in Computer Science;CH Mai,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unusual Transformation: A Deep Learning Approach to Create Art;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2022

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