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Handwritten Mathematical Expression Recognition via Paired Adversarial Learning | |
Jin-Wen Wu1,2![]() ![]() ![]() ![]() ![]() | |
发表期刊 | International Journal of Computer Vision
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ISSN | 0920-5691 |
2020 | |
卷号 | 128期号:128页码:2386-2401 |
通讯作者 | Wu, Jin-Wen(jinwen.wu@nlpr.ia.ac.cn) |
摘要 | Recognition of handwritten mathematical expressions (MEs) is an important problem that has wide applications in practice. HandwrittenME recognition is challenging due to the variety of writing styles andMEformats. As a result, recognizers trained by optimizing the traditional supervision loss do not perform satisfactorily. To improve the robustness of the recognizer with respect to writing styles, in this work, we propose a novel paired adversarial learning method to learn semantic-invariant features. Specifically, our proposed model, named PAL-v2, consists of an attention-based recognizer and a discriminator. During training, handwritten MEs and their printed templates are fed into PAL-v2 simultaneously. The attention-based recognizer is trained to learn semantic-invariant features with the guide of the discriminator. Moreover, we adopt a convolutional decoder to alleviate the vanishing and exploding gradient problems of RNN-based decoder, and further, improve the coverage of decoding with a novel attention method. We conducted extensive experiments on the CROHME dataset to demonstrate the effectiveness of each part of the method and achieved state-of-the-art performance. |
关键词 | Handwritten ME recognition Paired adversarial learning Semantic-invariant features Convolutional decoder Coverage of decoding |
DOI | 10.1007/s11263-020-01291-5 |
关键词[WOS] | RETRIEVAL |
URL | 查看原文 |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000572233600003 |
出版者 | SPRINGER |
七大方向——子方向分类 | 文字识别与文档分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40628 |
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 |
通讯作者 | Jin-Wen Wu |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation of Chinese Academy of Sciences, Beijing 100190, People’s Republic of China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China 3.CAS Center for Excellence of Brain Science and Intelligence Technology, Beijing 100190, People’s Republic of China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Jin-Wen Wu,Fei Yin,Yan-Ming Zhang,et al. Handwritten Mathematical Expression Recognition via Paired Adversarial Learning[J]. International Journal of Computer Vision,2020,128(128):2386-2401. |
APA | Jin-Wen Wu,Fei Yin,Yan-Ming Zhang,Xu-Yao Zhang,&Cheng-Lin Liu.(2020).Handwritten Mathematical Expression Recognition via Paired Adversarial Learning.International Journal of Computer Vision,128(128),2386-2401. |
MLA | Jin-Wen Wu,et al."Handwritten Mathematical Expression Recognition via Paired Adversarial Learning".International Journal of Computer Vision 128.128(2020):2386-2401. |
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