Deep convolutional neural networks for crack detection from image data
US10860879B2 · kind B2 · utility
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Key dates
| Filing date | May 16, 2016 |
| Grant date | Dec 8, 2020 |
| Priority date | — |
| Expiry date | Jul 26, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30164
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method includes detecting at least one region of interest in a frame of image data. One or more patches of interest are detected in the frame of image data based on detecting the at least one region of interest. A model including a deep convolutional neural network is applied to the one or more patches of interest. Post-processing of a result of applying the model is performed to produce a post-processing result for the one or more patches of interest. A visual indication of a classification of defects in a structure is output based on the result of the post-processing.
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