Lane Detection Network: Using Artificial Intelligence and Deep Learning

Divyanka ThakurDepartment of Computer Science Engineering (AI&ML), Smt. Indira Gandhi College of Engineering, Navi Mumbai, IndiaPriya PalDepartment of Computer Science Engineering (AI&ML), Smt. Indira Gandhi College of Engineering, Navi Mumbai, IndiaAmogh JadhavDepartment of Computer Science Engineering (AI&ML), Smt. Indira Gandhi College of Engineering, Navi Mumbai, IndiaNumaira KableDepartment of Computer Science Engineering (AI&ML), Smt. Indira Gandhi College of Engineering, Navi Mumbai, IndiaRadhika NandaDepartment of Computer Science Engineering (AI&ML), Smt. Indira Gandhi College of Engineering, Navi Mumbai, India

Vol 8 No 3 (2024): Volume 8, Issue 3, March 2024 | Pages: 328-331

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 18-04-2024

doi Logo doi.org/10.47001/IRJIET/2024.803050

Abstract

Lane detection, a pivotal technology in autonomous vehicles, involves the identification and tracking of lane markings on roadways using computer vision or image processing techniques. In this study, we utilize the Yolov8 semantic segmentation model to train our dataset. Our objective is to implement this solution road, with customized data sourced from different roads and highways. The model demonstrates exceptional accuracy, rendering it highly dependable for segmentation tasks. Even across a broader Intersection over Union (IoU) range (0.5:0.9), the model maintains a commendable mAP of 0.842.

Keywords

Lane Detection, Semantic Segmentation, Yolov8, Autonomous Vehicle, Indian Roadways


Citation of this Article

          

Divyanka Thakur, Priya Pal, Amogh Jadhav, Numaira Kable, Radhika Nanda, “Lane Detection Network: Using Artificial Intelligence and Deep Learning”, Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 8, Issue 3, pp 328-331, March 2024. Article DOI https://doi.org/10.47001/IRJIET/2024.803050

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