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.

Bibliographische Detailangaben
Hauptverfasser: Rabbi, Kazi Kamruzzaman, Dev, Pranto, Hossain, Akram, Sadman, Aninda
Weitere Verfasser: Rasel, Annajiat Alim
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Brac University 2023
Schlagworte:
Online Zugang:http://hdl.handle.net/10361/21880
id 10361-21880
record_format dspace
spelling 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
collection 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
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AT hossainakram kdanetopticalrecognitionforbanglalanguageusingdeepneuralnetworks
AT sadmananinda kdanetopticalrecognitionforbanglalanguageusingdeepneuralnetworks
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