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Title: Developing Japanese Ikebana as a Digital Painting Tool via AI
Authors: Cong Hung, Mai
Tosa, Naoko  kyouindb  KAKEN_id
Nakatsu, Ryohei
Author's alias: 土佐, 尚子
中津, 良平
Keywords: GANs
Cycle GAN
Digital art
Issue Date: 2020
Publisher: Springer, Cham
Journal title: Entertainment Computing - ICEC 2020
Start page: 297
End page: 307
Abstract: In this research, we have carried out various experiments to perform mutual transformation between a domain of Ikebana (Japanese traditional flower arrangement) photos and other domains of images (landscapes, animals, portraits) to create new artworks via CycleGAN, a variation of GANs (Generative Adversarial Networks) - new AI technology that can perform deep learning with less training data. With the capability of achieving transformation between two image sets using CycleGAN, we obtained several interesting results in which Ikebana plays the role of a digital painting tool due to the flexibility and minimality of the Japanese culture form. Our experiments show that Ikebana can be developed as a painting tool in digital art with the help of CycleGAN and opens a new way to create digital artworks of high-abstracted level by applying AI techniques to elements from traditional culture.
Description: [ICEC 2020]19th IFIP TC 14 International Conference, ICEC 2020, Xi'an, China, November 10–13, 2020, Proceedings
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12523)
Rights: This is a post-peer-review, pre-copyedit version of an article published in Entertainment Computing - ICEC 2020. The final authenticated version is available online at:
The full-text file will be made open to the public on 5 Janurary 2022 in accordance with publisher's 'Terms and Conditions for Self-Archiving'.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
DOI(Published Version): 10.1007/978-3-030-65736-9_27
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