Improving detection of asphalt distresses with deep learning-based diffusion model for intelligent road maintenance-Reference-Cited by-同舟云学术

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Improving detection of asphalt distresses with deep learning-based diffusion model for intelligent road maintenance

Published:2024-03 Issue: Volume:17 Page:100315
ISSN:2666-1659
Container-title:Developments in the Built Environment
language:en
Short-container-title:Developments in the Built Environment

Author:

Cano-Ortiz Saúl^ORCID,Lloret Iglesias Lara,Martinez Ruiz del Árbol Pablo,Castro-Fresno Daniel

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Materials Science (miscellaneous),Building and Construction,Civil and Structural Engineering,Architecture

Reference59 articles.

1. Pixel-level classification for bridge deck rebar detection and localization using multi-stage deep encoder-decoder network;Ahmed;Dev. Built Environ.,2023

2. Computer vision framework for crack detection of civil infrastructure—a review;Ai;Eng. Appl. Artif. Intell.,2023

3. A hybrid deep learning pavement crack semantic segmentation;Al-Huda;Eng. Appl. Artif. Intell.,2023

4. “Mosquitonet.” UCrea, Santander;Cano-Ortiz,2022

5. Machine learning algorithms for monitoring pavement performance;Cano-Ortiz;Autom. ConStruct.,2022

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

2. Road Surface Defect Detection Algorithm Based on YOLOv8;Electronics;2024-06-20

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