Ta et al., 2020 - Google Patents
Monitoring of corroded and loosened bolts in steel structures via deep learning and Hough transformsTa et al., 2020
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- 11747658944443400841
- Author
- Ta Q
- Kim J
- Publication year
- Publication venue
- Sensors
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Snippet
In this study, a regional convolutional neural network (RCNN)-based deep learning and Hough line transform (HLT) algorithm are applied to monitor corroded and loosened bolts in steel structures. The monitoring goals are to detect rusted bolts distinguished from non …
- 229910000831 Steel 0 title abstract description 26
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- G—PHYSICS
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- G06Q10/063—Operations research or analysis
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- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
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