Classification of defects in sewer pipes using neural networks

Journal of Infrastructure Systems

Volumn 6, Issue 3, 2000, Pages 97-104

  Moselhi, Osama ^a,b   Shehab Eldeen, Tariq ^b  

^a ASCE ^*  (Canada)

^b Gina Cody School of Engineering and Computer Science   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

UNDERGROUND SEWER PIPES;

ALGORITHMS; BACKPROPAGATION; CRACKS; DEFECTS; NEURAL NETWORKS;

SEWERS;

DEFECT; MAINTENANCE; NEURAL NETWORK; PIPELINE; SEWAGE;

EID: 0034283417     PISSN: 10760342     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)1076-0342(2000)6:3(97)     Document Type: Article

References (21)

1. Neural networks in civil engineering. I: Principles and understanding
2. Neural networks in civil engineering. II: Systems and applications
3. Developing practical neural network applications using back-propagation
4. Comparison of traditional and neural classification for pavement-crack detection
5. A neural network image classification system for automatic inspection
6. Selection methods for trenchless technologies
7. Small cameras: Diagnosing sewer lateral quickly and easily
8. Neural networks and their applications in civil engineering
9. Neural networks as tools in construction
10. Potential applications of neural networks in construction
11. Automated detection of defects in underground sewer and water pipes
12. Back-propagation networks configuration for blood vessels detection in angiograms
13. Digital image concepts and application in pavement management
14. Development of an intelligent system for automated pavement evaluation
15. Capabilities of four-layered feed-forward neural networks: Four layers versus three
16. Structural damage detection using artificial neural networks