Context-aware and boundary-optimized model for road marking instance segmentation using MLS point cloud intensity images
Accurate road marking extraction is essential for advancing digital transportation systems, autonomous vehicles, and high-definition maps. Although existing methods focus on extracting high-precision road markings from Mobile Laser Scanning (MLS) point clouds, they still face challenges in practical...
Saved in:
| Main Authors: | Dehui Li, Tao Liu, Ping Du, Tianen Ma, Shuangtong Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
|
| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2531842 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EDT-Net: A Lightweight Tunnel Water Leakage Detection Network Based on LiDAR Point Clouds Intensity Images
by: Zhenyu Liu, et al.
Published: (2025-01-01) -
Regulatory peculiarities of the use of road signs 5.15.1, 5.15.2 and marking 1.18 on road sections with traffic of fixed-route vehicles
by: G. V. Abakumov, et al.
Published: (2022-06-01) -
Street View Image-Based Road Marking Inspection System Using Computer Vision and Deep Learning Techniques
by: Junjie Wu, et al.
Published: (2024-12-01) -
Enhanced boundary perception and streamlined instance segmentation
by: Junyong Shi, et al.
Published: (2025-07-01) -
A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles
by: Chao-Li Meng, et al.
Published: (2025-05-01)