中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Simultaneous Script Identification and Handwriting Recognition via Multi-Task Learning of Recurrent Neural Networks

文献类型:会议论文

作者Chen, Zhuo1,2; Wu, Yichao1,2; Yin, Fei1; Liu, Chenglin1,2
出版日期2017
会议日期2017.11.9-15
会议地点Kyoto, Japan
关键词Multi-task Learning Sepmdlstm Script Identification Language Identification Handwritten Text Recognition
英文摘要In this paper, we propose a method for simultaneous script identification and handwritten text line recognition in multi-task learning framework. Firstly, we use Separable Multi-Dimensional Long Short-Term Memory (SepMDLSTM) to encode the input text line images based on convolutional feature extraction. Then, the extracted features are fed into two classification modules for script identification and multi-script text recognition, respectively. All the network parameters are trained end-to-end by multi-task learning where the script identification task and the text recognition task are aimed to minimize the Negative Log Likelihood (NLL) loss and Connectionist Temporal Classification (CTC) loss, respectively. We evaluated the performance of the proposed method on handwritten text line datasets of three languages, namely, IAM (English), Rimes (French) and IFN/ENIT (Arabic). Experimental results demonstrate the multitask learning framework performs superiorly for both script identification and text recognition. Particularly, the accuracy of script identification is higher than 99.9% and the character error rate (CER) of text recognition is even lower than that of some single-script text recognition systems.
语种英语
源URL[http://ir.ia.ac.cn/handle/173211/20012]  
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.中国科学院自动化研究所
2.中国科学院大学
推荐引用方式
GB/T 7714
Chen, Zhuo,Wu, Yichao,Yin, Fei,et al. Simultaneous Script Identification and Handwriting Recognition via Multi-Task Learning of Recurrent Neural Networks[C]. 见:. Kyoto, Japan. 2017.11.9-15.

入库方式: OAI收割

来源:自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。