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End to end Bangla handwritten and scene text detection using convolutional neural network

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dc.contributor.advisor Chakrabarty, Amitabha
dc.contributor.advisor Islam, Md Saiful
dc.contributor.author Mahal, Somania Nur
dc.contributor.author Abir, B M
dc.contributor.author Bakhtiar, Fahim
dc.date.accessioned 2018-01-11T09:56:17Z
dc.date.available 2018-01-11T09:56:17Z
dc.date.copyright 2017
dc.date.issued 2017-08-21
dc.identifier.other ID 13301124
dc.identifier.other ID 12201022
dc.identifier.other ID 16341028
dc.identifier.uri http://hdl.handle.net/10361/9032
dc.description This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. en_US
dc.description Cataloged from PDF version of thesis report.
dc.description Includes bibliographical references (pages 27-28).
dc.description.abstract Handwritten text detection from a natural image has a large set of difficulties. A systematic approach that can automatically recognise text from handwriting, printed books, road signs and also classifies text and nontext blocks from natural image has many significant applications. For instance, visual assistance for visually impaired people, image understanding, classification of text in image, implementing autonomous navigation system. Recent development of deep learning approach has strong capabilities to extract high level feature from a kernel(patch) of an Image. In this thesis we will demonstrate an alternate approach that integrates a multilayer convolutional neural network (CNN) with supervised feature learning .This approach allows a higher recall rate for the text in an image and thus increases the overall performances of the system. And we have used these methodologies to create a learning model using synthetic and real-world data that is capable to process bangla and english handwritten and scene text in natural image. en_US
dc.description.statementofresponsibility Somania Nur Mahal
dc.description.statementofresponsibility B M Abir
dc.description.statementofresponsibility Fahim Bakhtiar
dc.format.extent 28 pages
dc.language.iso en en_US
dc.publisher BRAC University en_US
dc.rights 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.
dc.subject Text detection en_US
dc.subject Neural network en_US
dc.subject Real-world data en_US
dc.subject Natural image en_US
dc.subject Nontext blocks en_US
dc.title End to end Bangla handwritten and scene text detection using convolutional neural network en_US
dc.type Thesis en_US
dc.contributor.department Department of Computer Science and Engineering, BRAC University
dc.description.degree B. Computer Science and Engineering


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