Joint Optimization of Crack Segmentation With an Adaptive Dynamic Threshold Module-Reference-Cited by-同舟云学术

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Joint Optimization of Crack Segmentation With an Adaptive Dynamic Threshold Module

Published:2024-07 Issue:7 Volume:25 Page:6902-6916
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Lei Qin¹^ORCID,Zhong Jiang¹^ORCID,Wang Chen¹^ORCID

Affiliation:

1. School of Computer Science, Chongqing University, Chongqing, China

Funder

National Natural Science Foundation of China

Chongqing Municipal Technology Innovation and Application Development Special Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10582787/10400886.pdf?arnumber=10400886

Reference62 articles.

1. What’s cracking? A review and analysis of deep learning methods for structural crack segmentation, detection and quantification;König;arXiv:2202.03714,2022

2. Crack Detection as a Weakly-Supervised Problem: Towards Achieving Less Annotation-Intensive Crack Detectors

3. An Automatic Image Processing Algorithm Based on Crack Pixel Density for Pavement Crack Detection and Classification

4. Segmentation-based deep-learning approach for surface-defect detection

5. PCDNet: Seed Operation–Based Deep Learning Model for Pavement Crack Detection on 3D Asphalt Surface

Cited by 1 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. A Review of Computer Vision-Based Crack Detection Methods in Civil Infrastructure: Progress and Challenges;Remote Sensing;2024-08-09

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