Automatic defogging, deblurring, and real-time segmentation system for sewer pipeline defects-Reference-Cited by-同舟云学术

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Automatic defogging, deblurring, and real-time segmentation system for sewer pipeline defects

Published:2022-12 Issue: Volume:144 Page:104595
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Ma Duo,Fang Hongyuan,Wang Niannian,Zheng Hangwei,Dong Jiaxiu,Hu Haobang

Publisher

Elsevier BV

Subject

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

Reference61 articles.

1. Automated decision making in highway pavement preventive maintenance based on deep learning;Li;Autom. Constr.,2022

2. A unified convolutional neural network integrated with conditional random field for pipe defect segmentation;Wang;Computer-Aided Civil Infrastruct. Eng.,2020

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

4. A robust instance segmentation framework for underground sewer defect detection;Li;Measurement,2022

5. A multi-defect detection system for sewer pipelines based on StyleGAN-SDM and fusion CNN;Ma;Constr. Build. Mater.,2021

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