Joint Training of Conditional Random Fields and Neural Networks for Stroke Classification in Online Handwritten Documents
Ye, Jun-Yu; Zhang, Yan-Ming; Liu, Cheng-Lin
2016
会议名称International Conference on Pattern Recognition
会议录名称23rd International Conference on Pattern Recognition
会议日期Dec. 04-08, 2016
会议地点Cancun, Mexico
摘要
The task of text/non-text stroke classification in online handwritten documents is an essential preprocessing step in document analysis. It is also a challenging problem since in many cases local features are not enough to generate high accuracy results and contextual information, such as temporal information and spatial information, must be carefully considered. In this paper, we propose a novel method, which jointly trains a combined model of conditional random fields and neural networks, to solve this problem. Both our unary and pairwise potentials are formulated as neural networks. The parameters of conditional random fields and neural networks are learned together during the training process. With much fewer parameters and faster speed, our method achieves impressive performance on the IAMonDo database, a publicly available database of freely handwritten documents.
关键词Crf
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12263
专题模式识别国家重点实验室_模式分析与学习
通讯作者Zhang, Yan-Ming
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Ye, Jun-Yu,Zhang, Yan-Ming,Liu, Cheng-Lin. Joint Training of Conditional Random Fields and Neural Networks for Stroke Classification in Online Handwritten Documents[C],2016.
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