Cross-modal Prototype Learning for Zero-shot Handwriting Recognition | |
Ao, Xiang1,3; Zhang, Xu-Yao1,3; Yang, Hong-Ming1,3; Yin, Fei1,3; Liu, Cheng-Lin1,2,3 | |
2019-09 | |
会议日期 | 20-25 Septemper 2019 |
会议地点 | Sydney, Australia |
关键词 | printed character handwritten character cross-modal prototype learning zero-shot |
英文摘要 | In contrast to machine recognizers that rely on training with large handwriting data, humans can recognize handwriting accurately on learning from few samples, and can even generalize to handwritten characters from printed samples. Simulating this ability in machine recognition is important to alleviate the burden of labeling large handwriting data, especially for large category set as in Chinese text. In this paper, inspired by human learning, we propose a cross-modal prototype learning (CMPL) method for zero-shot online handwritten character recognition: for unseen categories, handwritten characters can be recognized without learning from handwritten samples, but instead from printed characters. Particularly, the printed characters (one for each class) are embedded into a convolutional neural network (CNN) feature space to obtain prototypes representing each class, while the online handwriting trajectories are embedded with a recurrent neural network (RNN). Via cross-modal joint learning, handwritten characters can be recognized according to the printed prototypes. For unseen categories, handwritten characters can be recognized by only feeding a printed sample per category. Experiments on a benchmark Chinese handwriting database have shown the effectiveness and potential of the proposed method for zero-shot handwriting recognition. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/56731] |
专题 | 自动化研究所_模式识别国家重点实验室_模式分析与学习团队 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation of Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, P.R. China 2.CAS Center for Excellence in Brain Science and Intelligence Technology, Beijing 100049, P.R. China 3.University of Chinese Academy of Sciences, Beijing, P.R. China |
推荐引用方式 GB/T 7714 | Ao, Xiang,Zhang, Xu-Yao,Yang, Hong-Ming,et al. Cross-modal Prototype Learning for Zero-shot Handwriting Recognition[C]. 见:. Sydney, Australia. 20-25 Septemper 2019. |
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