Enhancing Lane Detection Performance A Comprehensive Analysis of YOLOPv2 under Adverse Conditions-Reference-Cited by-同舟云学术

Enhancing Lane Detection Performance A Comprehensive Analysis of YOLOPv2 under Adverse Conditions

Published:2024-05-25 Issue: Volume: Page:32-38
ISSN:
Container-title:Proceedings of the Cognitive Models and Artificial Intelligence Conference
language:
Short-container-title:

Author:

Mohamed Nour¹^ORCID,Shehada Dina²^ORCID,Bouridane Ahmed³^ORCID

Affiliation:

1. Electrical Engineering , University of Sharjah, United Arab Emirates

2. Electrical Engineering, University of Sharjah, United Arab Emirates

3. Computer Engineering, University of Sharjah, United Arab Emirates

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3660853.3660859

Reference12 articles.

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2. Real-Time Lane Detection by Using Biologically Inspired Attention Mechanism to Learn Contextual Information

3. Behavioral Intentions of Urban Rail Transit Passengers during the COVID-19 Pandemic in Tianjin, China: A Model Integrating the Theory of Planned Behavior and Customer Satisfaction Theory

4. N. J. Zakaria, M. I. Shapiai, R. A. Ghani, M. Yasin, M. Z. Ibrahim, and N. Wahid, “Lane detection in autonomous vehicles: A systematic review,” IEEE Access, 2023.

5. C. Han, Q. Zhao, S. Zhang, Y. Chen, Z. Zhang, and J. Yuan, “Yolopv2: Better, faster, stronger for panoptic driving perception,” arXiv preprint arXiv:2208.11434, 2022.