KDANet: optical recognition for Bangla language using deep neural networks
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
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Brac University
2023
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10361-218802023-10-25T21:02:22Z KDANet: optical recognition for Bangla language using deep neural networks Rabbi, Kazi Kamruzzaman Dev, Pranto Hossain, Akram Sadman, Aninda Rasel, Annajiat Alim Karim, Dewan Ziaul Department of Computer Science and Engineering, Brac University Character recognition Bangla OCR KDANet Computer vision Deep learning Convolutional neural networks Cognitive learning theory Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 45-46). When images of printed or handwritten are converted; be it mechanically or electronically to an editable text format, this is called optical character recognition. Bangla is one of the most complex languages as it has so many characters and digits. Moreover the Bangla language has about 300 composite characters. That is why the extraction of characters from images is more difficult for Bangla compared to other languages. Deep learning has recently developed good capabilities for extracting high-level features from an image kernel. This paper will propose a custom model KDANet and compare with some popular deep learning models that can recognize handwritten Bangla characters written in various and distinct handwriting styles. These systems learn more accurate and inclusive features from large-scale training datasets than earlier feature extraction techniques. Kazi Kamruzzaman Rabbi Pranto Dev Akram Hossain Aninda Sadman B.Sc. in Computer Science and Engineering 2023-10-25T04:00:26Z 2023-10-25T04:00:26Z 2022 2022-05 Thesis ID 18101625 ID 18101424 ID 18101416 ID 22141052 http://hdl.handle.net/10361/21880 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. 46 pages application/pdf Brac University |
institution |
Brac University |
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Institutional Repository |
language |
English |
topic |
Character recognition Bangla OCR KDANet Computer vision Deep learning Convolutional neural networks Cognitive learning theory Neural networks (Computer science) |
spellingShingle |
Character recognition Bangla OCR KDANet Computer vision Deep learning Convolutional neural networks Cognitive learning theory Neural networks (Computer science) Rabbi, Kazi Kamruzzaman Dev, Pranto Hossain, Akram Sadman, Aninda KDANet: optical recognition for Bangla language using deep neural networks |
description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. |
author2 |
Rasel, Annajiat Alim |
author_facet |
Rasel, Annajiat Alim Rabbi, Kazi Kamruzzaman Dev, Pranto Hossain, Akram Sadman, Aninda |
format |
Thesis |
author |
Rabbi, Kazi Kamruzzaman Dev, Pranto Hossain, Akram Sadman, Aninda |
author_sort |
Rabbi, Kazi Kamruzzaman |
title |
KDANet: optical recognition for Bangla language using deep neural networks |
title_short |
KDANet: optical recognition for Bangla language using deep neural networks |
title_full |
KDANet: optical recognition for Bangla language using deep neural networks |
title_fullStr |
KDANet: optical recognition for Bangla language using deep neural networks |
title_full_unstemmed |
KDANet: optical recognition for Bangla language using deep neural networks |
title_sort |
kdanet: optical recognition for bangla language using deep neural networks |
publisher |
Brac University |
publishDate |
2023 |
url |
http://hdl.handle.net/10361/21880 |
work_keys_str_mv |
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1814308841413672960 |