Lane line detection based on cross-convolutional hybrid attention mechanism
Abstract In order to enhance the accuracy and robustness of lane line recognition in dynamic and complex environments, this paper proposes a lane line detection model based on a cross-convolutional hybrid attention mechanism (CCHA-Net). Unlike traditional approaches that separately employ channel an...
Saved in:
| Main Authors: | Jianping Wen, Zhuang Zhao, Chenze Wang, Ze Sun, Chao Xu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-01167-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
HGLFNet: Hybrid Global Semantic and Local Detail Feature Network for Lane Detection
by: Lei Ding, et al.
Published: (2025-01-01) -
SGPLane: Efficient lane detection via sampled grid points for autonomous driving
by: Xuewei Tang, et al.
Published: (2025-07-01) -
Hybrid adaptive method for lane detection of degraded road surface condition
by: Khaled H. Almotairi
Published: (2022-09-01) -
Rearview Camera-Based Blind-Spot Detection and Lane Change Assistance System for Autonomous Vehicles
by: Yunhee Lee, et al.
Published: (2025-01-01) -
Development of Robust Lane-Keeping Algorithm Using Snow Tire Track Recognition in Snowfall Situations
by: Donghyun Kim, et al.
Published: (2024-12-01)