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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Bangali Handwritten characters classification using Deep Convolutional Neural Network

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    18301093, 18301116_CSE.pdf (1.354Mb)
    Date
    2022-05
    Publisher
    Brac University
    Author
    Sikder, Shihab Uddin
    Muslebeen, Md. Shafiul
    Metadata
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    URI
    http://hdl.handle.net/10361/17653
    Abstract
    Handwritten letter classification of any given language has the potential to be used in various fields such as literature, educational institutions, digitization of govern ment records etc. Bengali language with its complex sets of mixed characters, poses significant complexities in terms of automatic recognition of characters. In the Bengali character set, there are over 360 distinct characters among which a lot of similarities are present between different characters. Thus, the classification of these characters gets harder as the recognition system incorporates all these distinct characters. In recent years, a lot of research has been done to solve this problem on isolated datasets with significant results. Continuing the advancement in im age processing, In this paper, we have proposed a custom CNN model which has been trained on Bangla Lekha Isolated dataset containing 1,66,106 images belong to 84 distinct classes with the capability to detect individual handwritten Bengali letters including digits, vowels, consonants and compound characters with 93.15% accuracy while using less number of parameters compared to existing popular models
    Keywords
    Deep learning; CNN; Bangali characters; Image processing; DCNN; Handwritten character recognition; Bengali letters; Bengali compound characters.
     
    LC Subject Headings
    Deep learning (Machine learning); Neural network.; Neural networks (Computer science)
     
    Description
    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 37-40).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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