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The IUP Journal of Telecommunications

Track Detection System for Driving Using Image Processing and Deep Learning

Article Details

Pub. Date	: Feb' 2023
Product Name	: The IUP Journal of Telecommunications
Product Type	: Article
Product Code	: IJTC040223
Author Name	: Anand Dohare, Ajay Kumar Sahu, Swastika Sharma and Dushyant Bhati
Availability	: YES
Subject/Domain	: Arts & Humanities
Download Format	: PDF Format
No. of Pages	: 10

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Abstract

The development of intelligent motors heavily depends on lane detection. The paper proposes track detection to address issues like truncated detection accuracy of conventional techniques and poor real-time performance of sub-part of Machine Learning-based procedures. The proposed lane detection set of rules outperformed both traditional methods and Deep Learning-based methodologies in terms of accuracy, realtime performance, detection performance and interference resistance. Correct reputation cost and average processing time showed significant improvements. The provided set of guidelines is deemed to be essential for promoting the technological level of intelligent driver assistance and intelligent driver protection.

Introduction

Robotic cars have been a dream for automobile companies worldwide, and many of them have tried to develop one. In the past few decades, with the advent of many technology companies, the market for cars has started to expand. The aim of this paper is to use Deep Learning techniques to create a method that enables the car to be driven in the proper direction on the roads.