发布时间：

2026-06-30

所属单位：

人工智能教育学部

论文名称：

Improving Oracle Bone Characters Recognition via A CycleGAN-Based Data Augmentation Method

发表刊物：

国际计算机前沿大会会议论文集

刊物所在地：

国内外公开发行

关键字：

Learning algorithms

摘要：

Oracle bone inscription is the earliest writing system in China which contains rich information about the history of Shang dynasty. Automatically recognizing oracle bone characters is of great significance since it could promote the research on history, philology and archaeology. The proposed solutions for oracle bone characters recognition are mainly based on machine learning or deep learning algorithms which rely on a large number of supervised training data. However, the existing dataset suffers from the problem of severe class imbalance. In this work, we propose a CycleGAN-based data augmentation method to overcome the limitation. Via learning the mapping between the glyph images data domain and the real samples data domain, CycleGAN could generate oracle character images of high-quality. The quality is evaluated using the quantitative measure. Totally, 185362 samples are generated which could serve as a complementary to the existing dataset. With these generated samples, the state of the art results of recognition task on OBC306 are improved greatly in terms of mean accuracy and total accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

合写作者：

Zhao, Yiwen,Jin, Xinxin,Mouchere, Harold,余新国

第一作者：

王伟

论文类型：

会议论文

通讯作者：

张婷

论文编号：

1722785276637614080

文献类型：

00013

卷号：

1793 CCIS

ISSN号：

1865-0929

是否译文：

否

发表时间：

2023-04-01

收录刊物：

其他（ESI、Scopus、OA）、EI