An Analysis on Bengali handwritten conjunct character recognition and prediction
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
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| Формат: | Диссертация |
| Язык: | English |
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Brac University
2021
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| Online-ссылка: | http://hdl.handle.net/10361/15514 |
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10361-155142022-01-26T10:13:16Z An Analysis on Bengali handwritten conjunct character recognition and prediction Munawar, Maazin Roy, Yagghaseni Saha Hussain, Mohammed Mudabbir Islam, Md. Saiful Department of Computer Science and Engineering, Brac University Conjunct Characters Handwritten Neural Networks Bengali Segmentation ResNet-50 ShuffleNet LSTM GoogleNet Neural Networks This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 29-31). In the very active field of handwriting recognition, a lot of research can be found in the detection of the handwriting of various languages, especially English. However, for languages like Bengali, while they hold some success in handwritten character recognition, a big roadblock is Bengali conjunct characters or “Juktakkhor”. As Bengali conjunct characters are very complex, even today many institutions in Bangladesh still maintain documents as handwritten copies. In this paper, we will present a model that focuses on conjunct character recognition and conversion to textformat. OurproposedsystemwillbetrainedandtestedusingCNNmodelslike VGG19, ResNet-50, GoogleNet, LSTM, ShuffleNet etc. The results generated from preliminary analysis yield that ShuffleNet gives the most accurate results with an accuracy of 91.2% followed by GoogleNet with 73.3%. Maazin Munawar Yagghaseni Saha Roy Mohammed Mudabbir Hussain B. Computer Science 2021-10-21T09:01:52Z 2021-10-21T09:01:52Z 2021 2021-01 Thesis ID 17101036 ID 17101019 ID 17101350 http://hdl.handle.net/10361/15514 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 31 pages application/pdf Brac University |
| institution |
Brac University |
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Institutional Repository |
| language |
English |
| topic |
Conjunct Characters Handwritten Neural Networks Bengali Segmentation ResNet-50 ShuffleNet LSTM GoogleNet Neural Networks |
| spellingShingle |
Conjunct Characters Handwritten Neural Networks Bengali Segmentation ResNet-50 ShuffleNet LSTM GoogleNet Neural Networks Munawar, Maazin Roy, Yagghaseni Saha Hussain, Mohammed Mudabbir An Analysis on Bengali handwritten conjunct character recognition and prediction |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Islam, Md. Saiful |
| author_facet |
Islam, Md. Saiful Munawar, Maazin Roy, Yagghaseni Saha Hussain, Mohammed Mudabbir |
| format |
Thesis |
| author |
Munawar, Maazin Roy, Yagghaseni Saha Hussain, Mohammed Mudabbir |
| author_sort |
Munawar, Maazin |
| title |
An Analysis on Bengali handwritten conjunct character recognition and prediction |
| title_short |
An Analysis on Bengali handwritten conjunct character recognition and prediction |
| title_full |
An Analysis on Bengali handwritten conjunct character recognition and prediction |
| title_fullStr |
An Analysis on Bengali handwritten conjunct character recognition and prediction |
| title_full_unstemmed |
An Analysis on Bengali handwritten conjunct character recognition and prediction |
| title_sort |
analysis on bengali handwritten conjunct character recognition and prediction |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/15514 |
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1814308070804684800 |