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Co-operative College, Mandalay
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Kyaukse University
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Maubin University
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Mawlamyine University
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Meiktila University
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Mohnyin University
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Myanmar Institute of Information Technology
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Myanmar Maritime University
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National Management Degree College
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Naypyitaw State Academy
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Pathein University
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Sagaing University
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Sagaing University of Education
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Taunggyi University
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Technological University, Hmawbi
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Technological University (Kyaukse)
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Technological University Mandalay
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University of Computer Studies, Mandalay
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University of Computer Studies Maubin
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University of Computer Studies, Meikhtila
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University of Computer Studies Pathein
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University of Computer Studies, Taungoo
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University of Computer Studies, Yangon
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University of Dental Medicine Mandalay
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University of Dental Medicine, Yangon
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University of Information Technology
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University of Mandalay
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University of Medicine 1
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University of Medicine Mandalay
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University of Myitkyina
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University of Public Health, Yangon
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University of Veterinary Science
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University of Yangon
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West Yangon University
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Yadanabon University
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Yangon Technological University
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Yangon University of Distance Education
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Yangon University of Economics
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Yangon University of Education
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Yangon University of Foreign Languages
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Yezin Agricultural University
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New Index
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Item
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Mobile based Text Image Recognition using Deep Learning Approach
https://meral.edu.mm/records/3487
https://meral.edu.mm/records/34875486eeca-78cc-4774-a5bd-ca3c829d4dc1
0586d018-1356-42cd-a1b7-490b9be6d0d3
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Article | ||||||
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Publication | ||||||
Title | ||||||
Title | Mobile based Text Image Recognition using Deep Learning Approach | |||||
Language | en | |||||
Publication date | 2019-02-27 | |||||
Authors | ||||||
Maung, Saw Zay Maung | ||||||
Aye, Nyein | ||||||
Description | ||||||
Recognizing text image from mobile phone is achallenge task for limited capacity and processingpower. And also the accuracy of the system isimportant for text image recognition system. In thissystem, we aimed to develop a Text Image RecognitionSystem for mobile environment using MyanmarCharacter Dataset. Firstly, the image captured frommobile phone’s camera and then segment eachconnected character using Connected LabelingAlgorithm. After that the segmented characters inputinto the Convolutional Neural Network by passinglayer by layer to get feature maps for recognizing thewords in a given text image. | ||||||
Keywords | ||||||
Connected Labeling Algorithm, Convolutional Neural Network | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/1232 | |||||
Journal articles | ||||||
Seventeenth International Conference on Computer Applications(ICCA 2019) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |