基于多阶段数据生成的自循环文本智能识别

doi:10.16451/j.cnki.issn1003-6059.202005009

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Abstract

There are few effective big data annotation methods for both English and Chinese recognition in complex and diverse scenarios. Therefore, multi-stage data generation self-circulation training algorithm(MSDG-OCR) for complex and diverse text recognition scenarios is proposed. Text data is generated randomly according to the defined generated data parameters, and the data annotation process is omitted. Grounded on convolutional recurrent neural network(CRNN) model, multi-stage self-circulation training is carried out, and the recognition accuracy of the samples is continuously improved by controlling the data generation strategy during the loop process. Experiments show that the proposed.

Key words： Big Date Annotation Data Generation Text Recognition Convolutional Recurrent Neural Network(CRNN)

Received: 15 September 2019

ZTFLH:

TP 391.4

Fund:

Supported by Key Research and Development Program of Zhejiang Province(No.2019C01004), Key Research and Development Program of Guangdong Province(No.2019B010120001), Key Industrial Technology Development Project of Chongqing Development and Reform Commission(No.2018148208), Key Technological Innovation and Application Development Project of Chongqing(No.cstc2019jscx-fxydX0094), Innovation and Entrepreneurship Demonstration Team of Yingcai Program of Chongqing(No.CQYC201903167), Open Research Project of the State Key Laboratory of Industrial Control Technology of Zhejiang University(No.ICT170330,ICT1800413,ICT1900358)

About author:: (MA Xinqiang, Ph.D candidate, professor. His research interests include machine lear-ning and big data.);(LIU Lina, master student. Her research interests include deep learning and computer vision.);(LI Xuewei, master, senior economist. Her research interests include computer application technology.);(GU Ye, master, senior economist. His research interests include pattern recognition.);(HUANG Yi, Ph.D candidate, professor. Her research interests include artificial intelligence.);(LIU Yong(Corresponding author), Ph.D., professor. His research interests include robot and deep learning.)

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	MA Xinqiang
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Cite this article:

MA Xinqiang,LIU Lina,LI Xuewei等. Self-circulation Intelligent Text Recognition Based on Multi-stage Data Generation[J]. , 2020, 33(5): 468-476.

URL:

http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202005009 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2020/V33/I5/468

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