Vehicle model identification using neural network approaches

dc.contributor.advisorMostakim, Moin
dc.contributor.authorMojumder, Uttam
dc.contributor.authorSarker, Toqi Tahamid
dc.contributor.authorMonika, Gulnahar Mahbub
dc.contributor.authorRatul, Nurul Amin
dc.date.accessioned2017-01-31T04:16:00Z
dc.date.available2017-01-31T04:16:00Z
dc.date.issued12/14/2016
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 42-43).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
dc.description.abstractOur 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.
dc.identifier.otherID 11110005
dc.identifier.otherID 12201007
dc.identifier.otherID 12201089
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/14d4c9e1-628a-4632-b763-c1c7fa3924d3
dc.identifier.urihttp://hdl.handle.net/10361/7715
dc.language.isoen
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectVehicle model identification
dc.subjectNeural network approaches
dc.titleVehicle model identification using neural network approaches
dc.typeThesis

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