Object and Lane Detection Technique for Autonomous Car Using Machine Learning Approach
The main objective of this work is to develop a perception algorithm for self-driving cars which is based on pure vision data or camera data. The work is divided into two major parts. In part one of the work, we develop a powerful and robust lane detection algorithm which can determine the safely dr...
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oai:doaj.org-article:7ba87448c3a94c668c8c9530113fdeea2021-12-05T14:11:11ZObject and Lane Detection Technique for Autonomous Car Using Machine Learning Approach1407-617910.2478/ttj-2021-0029https://doaj.org/article/7ba87448c3a94c668c8c9530113fdeea2021-11-01T00:00:00Zhttps://doi.org/10.2478/ttj-2021-0029https://doaj.org/toc/1407-6179The main objective of this work is to develop a perception algorithm for self-driving cars which is based on pure vision data or camera data. The work is divided into two major parts. In part one of the work, we develop a powerful and robust lane detection algorithm which can determine the safely drive-able region in front of the car. In part two we develop and end to end driving model based on CNNs to learn from the drivers driving data and can drive the car with only the camera data from on-board cameras. Performance of the proposed system is observed by the implementation of the autonomous car that can be able to detect and classify the stop signs and other vehicles.Muthalagu RajaBolimera Anudeep SekharDuseja DhruvFernandes ShaunSciendoarticleimage processingmachine learningautonomous carsself-drivingobject detectionTransportation and communicationK4011-4343ENTransport and Telecommunication, Vol 22, Iss 4, Pp 383-391 (2021) |
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image processing machine learning autonomous cars self-driving object detection Transportation and communication K4011-4343 |
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image processing machine learning autonomous cars self-driving object detection Transportation and communication K4011-4343 Muthalagu Raja Bolimera Anudeep Sekhar Duseja Dhruv Fernandes Shaun Object and Lane Detection Technique for Autonomous Car Using Machine Learning Approach |
description |
The main objective of this work is to develop a perception algorithm for self-driving cars which is based on pure vision data or camera data. The work is divided into two major parts. In part one of the work, we develop a powerful and robust lane detection algorithm which can determine the safely drive-able region in front of the car. In part two we develop and end to end driving model based on CNNs to learn from the drivers driving data and can drive the car with only the camera data from on-board cameras. Performance of the proposed system is observed by the implementation of the autonomous car that can be able to detect and classify the stop signs and other vehicles. |
format |
article |
author |
Muthalagu Raja Bolimera Anudeep Sekhar Duseja Dhruv Fernandes Shaun |
author_facet |
Muthalagu Raja Bolimera Anudeep Sekhar Duseja Dhruv Fernandes Shaun |
author_sort |
Muthalagu Raja |
title |
Object and Lane Detection Technique for Autonomous Car Using Machine Learning Approach |
title_short |
Object and Lane Detection Technique for Autonomous Car Using Machine Learning Approach |
title_full |
Object and Lane Detection Technique for Autonomous Car Using Machine Learning Approach |
title_fullStr |
Object and Lane Detection Technique for Autonomous Car Using Machine Learning Approach |
title_full_unstemmed |
Object and Lane Detection Technique for Autonomous Car Using Machine Learning Approach |
title_sort |
object and lane detection technique for autonomous car using machine learning approach |
publisher |
Sciendo |
publishDate |
2021 |
url |
https://doaj.org/article/7ba87448c3a94c668c8c9530113fdeea |
work_keys_str_mv |
AT muthalaguraja objectandlanedetectiontechniqueforautonomouscarusingmachinelearningapproach AT bolimeraanudeepsekhar objectandlanedetectiontechniqueforautonomouscarusingmachinelearningapproach AT dusejadhruv objectandlanedetectiontechniqueforautonomouscarusingmachinelearningapproach AT fernandesshaun objectandlanedetectiontechniqueforautonomouscarusingmachinelearningapproach |
_version_ |
1718371306936729600 |