Towards an automated condition assessment framework of underground sewer pipes based on closed-circuit television (CCTV) images

A Survey on Image-Based Automation of CCTV and SSET Sewer Inspections

(2020) Joakim Bruslund Haurum et al.   AUTOMATION IN CONSTRUCTION

Crack Automatic Detection of CCTV Video of Sewer Inspection with Low Resolution

(2019) Gwanghee Heo et al.   KSCE Journal of Civil Engineering

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

(2019) Duanshun Li et al.   AUTOMATION IN CONSTRUCTION

A unified convolutional neural network integrated with conditional random field for pipe defect segmentation

(2019) Mingzhu Wang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Underground sewer pipe condition assessment based on convolutional neural networks

(2019) Syed Ibrahim Hassan et al.   AUTOMATION IN CONSTRUCTION

An integrated underground utility management and decision support based on BIM and GIS

(2019) Mingzhu Wang et al.   AUTOMATION IN CONSTRUCTION

A deep learning-based framework for an automated defect detection system for sewer pipes

(2019) Xianfei Yin et al.   AUTOMATION IN CONSTRUCTION

Deep Learning–Based Automated Detection of Sewer Defects in CCTV Videos

(2019) Srinath Shiv Kumar et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks

(2018) Srinath S. Kumar et al.   AUTOMATION IN CONSTRUCTION

Utilizing text recognition for the defects extraction in sewers CCTV inspection videos

(2018) L. Minh Dang et al.   COMPUTERS IN INDUSTRY

Automated detection of faults in sewers using CCTV image sequences

(2018) Joshua Myrans et al.   AUTOMATION IN CONSTRUCTION

Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques

(2018) Jack C.P. Cheng et al.   AUTOMATION IN CONSTRUCTION

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Integrated Vision-Based System for Automated Defect Detection in Sewer Closed Circuit Television Inspection Videos

(2015) Mahmoud R. Halfawy et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines

(2014) Tung-Ching Su et al.   SENSORS

Automated defect detection in sewer closed circuit television images using histograms of oriented gradients and support vector machine

(2013) Mahmoud R. Halfawy et al.   AUTOMATION IN CONSTRUCTION

Efficient Algorithm for Crack Detection in Sewer Images from Closed-Circuit Television Inspections

(2013) Mahmoud R. Halfawy et al.   Journal of Infrastructure Systems

Morphological segmentation based on edge detection for sewer pipe defects on CCTV images

(2011) Tung-Ching Su et al.   EXPERT SYSTEMS WITH APPLICATIONS

A morphological approach to pipe image interpretation based on segmentation by support vector machine

(2010) John Mashford et al.   AUTOMATION IN CONSTRUCTION

LabelMe: Online Image Annotation and Applications

(2010) Antonio Torralba et al.   PROCEEDINGS OF THE IEEE

Segmenting ideal morphologies of sewer pipe defects on CCTV images for automated diagnosis

(2008) Ming-Der Yang et al.   EXPERT SYSTEMS WITH APPLICATIONS

Automated diagnosis of sewer pipe defects based on machine learning approaches

(2007) Ming-Der Yang et al.   EXPERT SYSTEMS WITH APPLICATIONS