CASIA OpenIR  > 数字内容技术与服务研究中心  > 听觉模型与认知计算
Uyghur Text Matching in Graphic Images for Biomedical Semantic Analysis
Fang, Shancheng1,2; Xie, Hongtao3; Chen, Zhineng4; Liu, Yizhi5; Li, Yan6
AbstractHow to read Uyghur text from biomedical graphic images is a challenge problem due to the complex layout and cursive writing of Uyghur. In this paper, we propose a system that extracts text from Uyghur biomedical images, and matches the text in a specific lexicon for semantic analysis. The proposed system possesses following distinctive properties: first, it is an integrated system which firstly detects and crops the Uyghur text lines using a single fully convolutional neural network, and then keywords in the lexicon are matched by a well-designed matching network. Second, to train the matching network effectively an online sampling method is applied, which generates synthetic data continually. Finally, we propose a GPU acceleration scheme for matching network to match a complete Uyghur text line directly rather than a single window. Experimental results on benchmark dataset show our method achieves a good performance of F-measure 74.5%. Besides, our system keeps high efficiency with 0.5s running time for each image due to the GPU acceleration scheme.
KeywordUyghur Text Detection Text Recognition Text Extracting
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
Indexed BySCI
Funding OrganizationNational Nature Science Foundation of China(61771468 ; Youth Innovation Promotion Association Chinese Academy of Sciences(2017209) ; 61772526)
WOS Research AreaComputer Science ; Neurosciences & Neurology
WOS SubjectComputer Science, Interdisciplinary Applications ; Neurosciences
WOS IDWOS:000441590600016
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Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Informat Engn, Natl Engn Lab Informat Secur Technol, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Cyber Secur, Beijing, Peoples R China
3.Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei, Anhui, Peoples R China
4.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
5.Hunan Univ Sci & Technol, Sch Comp Sci & Engn, Xiangtan, Peoples R China
6.Beijing Kuaishou Technol Co Ltd, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Fang, Shancheng,Xie, Hongtao,Chen, Zhineng,et al. Uyghur Text Matching in Graphic Images for Biomedical Semantic Analysis[J]. NEUROINFORMATICS,2018,16(3-4):445-455.
APA Fang, Shancheng,Xie, Hongtao,Chen, Zhineng,Liu, Yizhi,&Li, Yan.(2018).Uyghur Text Matching in Graphic Images for Biomedical Semantic Analysis.NEUROINFORMATICS,16(3-4),445-455.
MLA Fang, Shancheng,et al."Uyghur Text Matching in Graphic Images for Biomedical Semantic Analysis".NEUROINFORMATICS 16.3-4(2018):445-455.
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