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Writer Adaptation with Style Transfer Mapping | |
Zhang, Xu-Yao; Liu, Cheng-Lin | |
发表期刊 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE |
2013-07-01 | |
卷号 | 35期号:7页码:1773-1787 |
文章类型 | Article |
摘要 | Adapting a writer-independent classifier toward the unique handwriting style of a particular writer has the potential to significantly increase accuracy for personalized handwriting recognition. This paper proposes a novel framework of style transfer mapping (STM) for writer adaptation. The STM is a writer-specific class-independent feature transformation which has a closed-form solution. After style transfer mapping, the data of different writers are projected onto a style-free space, where the writer-independent classifier needs no change to classify the transformed data and can achieve significantly higher accuracy. The framework of STM can be combined with different types of classifiers for supervised, unsupervised, and semi-supervised adaptation, where writer-specific data can be either labeled or unlabeled and need not cover all classes. In this paper, we combine STM with the state-of-the-art classifiers for large-category Chinese handwriting recognition: learning vector quantization (LVQ) and modified quadratic discriminant function (MQDF). Experiments on the online Chinese handwriting database CASIA-OLHWDB demonstrate that STM-based adaptation is very efficient and effective in improving classification accuracy. Semi-supervised adaptation achieves the best performance, while unsupervised adaptation is even better than supervised adaptation. On handwritten text data, semi-supervised adaptation achieves error reduction rates 31.95 and 25.00 percent by LVQ and MQDF, respectively. |
关键词 | Writer Adaptation Style Transfer Mapping Handwriting Recognition |
WOS标题词 | Science & Technology ; Technology |
关键词[WOS] | HANDWRITTEN CHARACTER-RECOGNITION ; CLASSIFICATION ; CLASSIFIERS ; MODELS |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000319060600018 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/3072 |
专题 | 多模态人工智能系统全国重点实验室_模式分析与学习 |
作者单位 | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Zhang, Xu-Yao,Liu, Cheng-Lin. Writer Adaptation with Style Transfer Mapping[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2013,35(7):1773-1787. |
APA | Zhang, Xu-Yao,&Liu, Cheng-Lin.(2013).Writer Adaptation with Style Transfer Mapping.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,35(7),1773-1787. |
MLA | Zhang, Xu-Yao,et al."Writer Adaptation with Style Transfer Mapping".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 35.7(2013):1773-1787. |
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XYZ2013-style_transf(2689KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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