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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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    Vehicle model identification using neural network approaches

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    11110005, 12201007, 12201089 & 13201033_CSE.pdf (3.351Mb)
    Date
    12/14/2016
    Publisher
    BRAC University
    Author
    Mojumder, Uttam
    Sarker, Toqi Tahamid
    Monika, Gulnahar Mahbub
    Ratul, Nurul Amin
    Metadata
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    URI
    http://hdl.handle.net/10361/7715
    Abstract
    Our world is going through a constant phase of growth and advancement where the manufacture of vehicles has increased exponentially. Vehicles of different brands with different features and models are vastly available in all over the world. Along with the fact that vehicles are now a basic need, every individual is now able to afford a vehicle of their choice and status. Consequently, misdemeanors such as theft, accidents, damage done, relating to automobiles has also increased over the years. Identifying a specific model vehicle among these several brands of vehicles can be considered difficult. Our main goal is to find the details of a specific model of a transport from several unknown automobile’s datasets. Our system will help to identify a vehicle and its model using still pictures of any brand of car. We hope that in future we can extend it to a more advanced identifying system which can be used by the government to reduce all forms of transgressions towards vehicles.
    Keywords
    Vehicle model identification; Neural network approaches
     
    Description
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 42-43).
     
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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