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dc.contributor.advisorUddin, Jia
dc.contributor.authorHussain, Shoumin Rafsun
dc.contributor.authorNelema, Mahima Noor
dc.contributor.authorKabir, Fahim M
dc.contributor.authorPatwary, Mohammad Rasheduzzaman
dc.date.accessioned2021-05-29T07:57:59Z
dc.date.available2021-05-29T07:57:59Z
dc.date.copyright2020
dc.date.issued2020-04
dc.identifier.otherID 16101043
dc.identifier.otherID 20341035
dc.identifier.otherID 16101047
dc.identifier.otherID 16101023
dc.identifier.urihttp://dspace.bracu.ac.bd/xmlui/handle/10361/14438
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 32-33).
dc.description.abstractHandwritten character recognition is a process of a system to access handwritten material from various sources such as paper records, photographs, touch screen apps, etc. The identification of handwritten and electronic character is a growing area of study and has wide uses in banks, offices and industries. Our Main purpose for this initiative is to develop an professional framework for the defense Indus tries. In this method a specific character of languages can be effectively identified by following a sequence using neural network. Neural computers in corporate data parallelism, and run from the processing of an ordinary computer in a special way. Developments of a certain desirable quality which classifies the input data into classes are made by neural computers after the starting state information is obtained.en_US
dc.description.statementofresponsibilityShoumin Rafsun Hussain
dc.description.statementofresponsibilityMahima Noor Nelema
dc.description.statementofresponsibilityFahim M Kabir
dc.description.statementofresponsibilityMohammad Rasheduzzaman Patwary
dc.format.extent33 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac 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.subjectCharacter recognitionen_US
dc.subjectHandwritten characteren_US
dc.subjectProfessional Frame-worken_US
dc.subjectSecurity Parallelismen_US
dc.subjectNeural Networken_US
dc.subject.lcshNeural networks (Computer science)
dc.titleHandwritten character recognition using neural networken_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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