Multi-scale context feature and cross-attention network-enabled system and software-based for pavement crack detection-Reference-Cited by-同舟云学术

Multi-scale context feature and cross-attention network-enabled system and software-based for pavement crack detection

Published:2024-01 Issue: Volume:127 Page:107328
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wen Xin^ORCID,Li Shuo^ORCID,Yu Hao,He Yu

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference47 articles.

1. Frequency-tuned salient region detection;Achanta;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2009

2. Automatic crack detection on two-dimensional pavement images: an algorithm based on minimal path selection. IEEE trans. Intell. Transp;Amhaz;Off. Syst.,2016

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Defect detection on multi-type rail surfaces via IoU decoupling and multi-information alignment;Advanced Engineering Informatics;2024-10

2. Enhancing pavement crack segmentation via semantic diffusion synthesis model for strategic road assessment;Results in Engineering;2024-09

3. EHSGNet: A novel edge and high-level semantic guided network for CFRP subsurface defects detection;Measurement;2024-09

4. Real-time pavement temperature prediction through ensemble machine learning;Engineering Applications of Artificial Intelligence;2024-09

5. Improving Pavement Crack Segmentation Using Attention Mechanism and Self-gated Activation;2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2024-08-06