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  2020, Vol. 33 Issue (5): 468-476    DOI: 10.16451/j.cnki.issn1003-6059.202005009
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Self-circulation Intelligent Text Recognition Based on Multi-stage Data Generation
MA Xinqiang1,2,3, LIU Lina2, LI Xuewei4, GU Ye4, HUANG Yi1,2,3, LIU Yong2
1. College of Computer Science and Technology, Guizhou University, Guiyang 550025;
2. Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027;
3. Institute of Intelligent Computing and Visualization Based on Big Data, Chongqing University of Arts and Sciences, Chong-qing 402160;
4. Material Branch, State Grid Zhejiang Electric Power Co.Ltd., Hangzhou 310000algorithm gains good recognition performance in multiple public English datasets and Chinese-specific complex text scenarios.

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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 wordsBig 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.
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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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