The Restoration of Style Chinese Characters Based on Deep Learning
Authors
Da Lv, Yijun Liu
Corresponding Author
Da Lv
Available Online May 2018.
- DOI
- 10.2991/ncce-18.2018.67How to use a DOI?
- Keywords
- Deep learning; generative adversarial network; structure generated clear.
- Abstract
For the image inpainting using incomplete Chinese characters proposed a new method for Chinese characters repair, the first use of U-Net type network structure combining the training method of generating against network design a style Chinese characters converter, and then repair the missing content by Chinese characters style converter. The experimental results show that the structure of the Chinese characters for the repair of the clear, less noise, edge connection also smooth, look real. This paper provides a new idea for image inpainting, it can be converted from other images to the same style of image for image recovery.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Da Lv AU - Yijun Liu PY - 2018/05 DA - 2018/05 TI - The Restoration of Style Chinese Characters Based on Deep Learning BT - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018) PB - Atlantis Press SP - 426 EP - 430 SN - 1951-6851 UR - https://doi.org/10.2991/ncce-18.2018.67 DO - 10.2991/ncce-18.2018.67 ID - Lv2018/05 ER -