CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer
Lining cracking is among the most prevalent forms of tunnel distress, posing significant threats to tunnel operations and vehicular safety. The segmentation of tunnel lining cracks is often hindered by the influence of complex environmental factors, which makes relying solely on local feature extrac...
Saved in:
Main Authors: | Kai Liu, Tao Ren, Zhangli Lan, Yang Yang, Rong Liu, Yuantong Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Buildings |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-5309/15/2/197 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EventSegNet: Direct Sparse Semantic Segmentation from Event Data
by: Pengju Li, et al.
Published: (2024-12-01) -
Performance and Efficiency Comparison of U-Net and Ghost U-Net in Road Crack Segmentation with Floating Point and Quantization Optimization
by: Haidhi Angkawijana Tedja, et al.
Published: (2024-12-01) -
AFN-Net: Adaptive Fusion Nucleus Segmentation Network Based on Multi-Level U-Net
by: Ming Zhao, et al.
Published: (2025-01-01) -
Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process
by: Akshansh Mishra, et al.
Published: (2023-01-01) -
Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process
by: Akshansh Mishra, et al.
Published: (2022-12-01)