Detection algorithm of defects on polyethylene gas pipe using image recognition

Classifying cracks at sub-class level in closed circuit television sewer inspection videos

(2020) Xin Zuo et al.   AUTOMATION IN CONSTRUCTION

Pipeline image diagnosis algorithm based on neural immune ensemble learning

(2020) Xiao Yu et al.   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING

A novel tunnel-lining crack recognition system based on digital image technology

(2020) Mingfeng Lei et al.   TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY

Pipeline image segmentation algorithm and heat loss calculation based on gene-regulated apoptosis mechanism

(2019) Xiao Yu et al.   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING

Detection and Isolation of Interior Defects Based on Image Processing and Neural Networks: HDPE Pipeline Case Study

(2018) Shiva Safari et al.   Journal of Pipeline Systems Engineering and Practice

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

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

Automatic weld defect identification from radiographic images

(2013) O. Zahran et al.   NDT & E INTERNATIONAL

Automatic weld defect detection based on potential defect tracking in real-time radiographic image sequence

(2011) Jiaxin Shao et al.   NDT & E INTERNATIONAL

Automatic detection of defects on polyethylene pipe welding using thermal infrared imaging

(2010) R. Kafieh et al.   INFRARED PHYSICS & TECHNOLOGY

Automated defect detection for sewer pipeline inspection and condition assessment

(2009) W. Guo et al.   AUTOMATION IN CONSTRUCTION

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

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

Reliability of non-destructive test techniques in the inspection of pipelines used in the oil industry

(2008) A.A. Carvalho et al.   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING

Automated diagnosis of sewer pipe defects based on machine learning approaches

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