Mostakim, MoinMojumder, UttamSarker, Toqi TahamidMonika, Gulnahar MahbubRatul, Nurul Amin2017-01-312017-01-31201612/14/2016ID 13201033ID 11110005ID 12201007ID 12201089http://hdl.handle.net/10361/7715Cataloged 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.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.43 pagesenBRAC University thesis 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.Vehicle model identificationNeural network approachesThesis