Sewer damage detection from imbalanced CCTV inspection data using deep convolutional neural networks with hierarchical classification-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Sewer damage detection from imbalanced CCTV inspection data using deep convolutional neural networks with hierarchical classification

Published:2019-05 Issue: Volume:101 Page:199-208
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Li Duanshun,Cong Anran,Guo Shuai

Funder

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference44 articles.

1. Innovative method for assessment of underground sewer pipe condition;Koo;Autom. Constr.,2006

2. State of the art review of inspection technologies for condition assessment of water pipes;Liu;Meas.: J. Int. Meas. Confederation,2013

3. Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks;Kumar;Autom. Constr.,2018

4. An evaluation of condition assessment protocols for sewer management;Rahman,2004

5. Automated defect detection tool for closed circuit television (CCTV) inspected sewer pipelines;Hawari;Autom. Constr.,2018

Cited by 119 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. Intelligent circumferential deformation prediction of structures in PCCP-E with a large diameter under internal water overpressure based on prototype experiments and Inception-ResNet-LSTM;Engineering Structures;2024-08

2. PipeTransUNet: CNN and Transformer fusion network for semantic segmentation and severity quantification of multiple sewer pipe defects;Applied Soft Computing;2024-07

3. A survey of deep learning-driven architecture for predictive maintenance;Engineering Applications of Artificial Intelligence;2024-07

4. Towards Geometric Digital Twins, Including Damage Detection, from Photos of Residential Buildings Facades;2024 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv);2024-06-12

5. Attention-ResNet-AR-LSTM: An intelligent method for PCCP deformation prediction via structure monitoring based on distributed fiber optics;Engineering Failure Analysis;2024-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3