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%
Description
Submitted by
Abid Hossain
T-181013