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Bangla Handwritten Character Recognition using Convolutional Neural Network with Data Augmentation
Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
University of Chittagong, Bangladesh.ORCID-id: 0000-0002-7473-8185
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. (Mobile and Pervasive Computing)ORCID-id: 0000-0002-3090-7645
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0003-0244-3561
Vise andre og tillknytning
2019 (engelsk)Inngår i: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), 2019Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper proposes a process of Handwritten Character Recognition to recognize and convert images of individual Bangla handwritten characters into electronically editable format, which will create opportunities for further research and can also have various practical applications. The dataset used in this experiment is the BanglaLekha-Isolated dataset [1]. Using Convolutional Neural Network, this model achieves 91.81% accuracy on the alphabets (50 character classes) on the base dataset, and after expanding the number of images to 200,000 using data augmentation, the accuracy achieved on the test set is 95.25%. The model was hosted on a web server for the ease of testing and interaction with the model. Furthermore, a comparison with other machine learning approaches is presented.

sted, utgiver, år, opplag, sider
2019.
Emneord [en]
Convolutional Neural Network, handwritten character recognition, Bangla handwritten characters, Data augmentation
HSV kategori
Forskningsprogram
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Identifikatorer
URN: urn:nbn:se:ltu:diva-73307OAI: oai:DiVA.org:ltu-73307DiVA, id: diva2:1298999
Konferanse
Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), 26 - 29 April 2019, Spokane, United States
Prosjekter
A belief-rule-based DSS to assess flood risks by using wireless sensor networks
Forskningsfinansiär
Swedish Research Council, 2014-4251Tilgjengelig fra: 2019-03-25 Laget: 2019-03-25 Sist oppdatert: 2019-04-02bibliografisk kontrollert

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Islam, Raihan UlAndersson, Karl

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