Deep Learning Based Vehicle Classification System using Convolutional Neural Network

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Date

2022-11

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Department of Electronic and Telecommunication Engineering

Abstract

The artificial neural network model known as the convolution neural network (CNN) has become particularly popular in computer vision applications. We introduced a convolution neural network for classification typical cars in this research study. Vehicle classification is essential for many applications, including traffic control systems and surveillance security systems. We used deep learning-based vehicle classification to classify the car. Our total dataset 17760 and the CNN was trained with 14216 input images in the training part while 3554 images were used in the testing part. Using parameters that are learned from the training data, we construct a convolutional neural network (CNN) model. The system shows quite good performance on standard dataset. The accuracy of the method we mentioned for classifying vehicles is 97%

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Submitted by Abid Hossain T-181013

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