Abstract
Any machine that moves people or goods qualifies as a vehicle. Vehicles include automobiles, bicycles, buses, aircraft, space shuttles, and a wide variety of others. A practical application of machine learning principles is vehicle detection and vehicle type recognition, which is directly applicable for a variety of operations in a traffic surveillance system and contributes to an intelligent traffic surveillance system. The processing of automatic vehicle identification and recognition using datasets of static images will be covered in this study. The surveillance system features moving vehicle detection and recognition, vehicle count, and permission verification with the organisation. Considering that algorithms are crucial to any machine learning programme, it is crucial that we select the optimum model for our project.
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