Integrated Deep Learning Solution and Fuzzy Logic for Accurate Vehicle Detection and Classification

Abstract

Vehicle detection plays an important role in the smart transportation system. It also played a significant role in various aspects like Traffic monitoring and management, Autonomous vehicles and Robotics, Surveillance and Security, advanced driver Assistance systems, Fleet Management, and Asset tracking. Also plays a critical role in various aspects of modern life, contributing to traffic efficiency, safety, security, and automation. The primary objective of this project is to examine the development and implementation of neural network models to predict vehicle models and detect vehicles within images.A number of typical network models have been applied in this training and classification experiments such as CNN (Convolutional Neural Network features), Classification model, and Fuzzy logic. This model will try to classify the vehicle with more accuracy.