Real-Time Vehicle Classification Using CNN

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Date

2020

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Scopus

Abstract

Convolutional Neural Network (CNN) is a model of artificial neural networks that has grown to be most well known in computer vision assignment. In this paper work, we presented convolutional neural network for classifying four types of common vehicle in our country. Vehicle classification plays a vital role of various application such as surveillance security system, traffic control system. We addressed these issues and fixed an aim to find a solution to reduce road accident due to traffic related cases. The greatest challenge of computer vision is to achieve effective results to implement a system due to variation in shapes and colors of data. To classify the vehicle we used two methods feature extraction and classification. These two methods can straightforwardly performed by convolutional neural network. The method shows quite good performance on real-time standard dataset. Our mentioned method able to reach 97% accuracy in case of vehicle classification.

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Vehicle, Machine learning, Image processing, CNN, Computer Vision

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