A support vector machine model for pipe crack size classification
Classifying pipe cracks by size from their pulse-echo ultrasonic signal is difficult but highly significant for the defect evaluation required in pipe testing and maintenance decision making. For this thesis, a binary Support Vector Machine (SVM) classifier, which divides pipe cracks into two categ...
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| Format: | Others |
| Language: | en |
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2009
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| Online Access: | http://hdl.handle.net/10048/400 |