DocumentCode
328395
Title
Syntactic pattern recognition by quadratic neural nets. A case study: rail flaw classification
Author
McKenzie, Patricia ; Alder, Mike
Author_Institution
Centre for Intelligent Inf. Process. Syst., Western Australia Univ., Nedlands, WA, Australia
Volume
3
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
2101
Abstract
We show how quadratic neural nets can be used to accomplish syntactic pattern recognition. The method has been applied successfully to an industrial problem of classifying rail flaws by examining ultrasonic images.
Keywords
civil engineering computing; engineering; flaw detection; image classification; neural nets; railways; ultrasonic imaging; ultrasonic materials testing; industrial problem; quadratic neural nets; rail flaw classification; syntactic pattern recognition; ultrasonic images; Computer aided software engineering; Covariance matrix; Fasteners; Information processing; Intelligent systems; Mathematics; Neural networks; Pattern recognition; Rails; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.714138
Filename
714138
Link To Document