Method and system for surface defect detection based on few-shot learning
US12190492B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 5, 2024 |
| Grant date | Jan 7, 2025 |
| Priority date | — |
| Expiry date | Jul 5, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A surface defect detection method for a primary cable of an aerostat based on few-shot learning includes the following steps. A hardware and software system environment is set. A surface image of the primary cable is acquired and processed to obtain augmented surface image data, which is labeled to construct a surface defect sample library. A defect detection network model is designed and constructed, and then is trained based on the surface defect sample library. A query set in the surface defect sample library is processed with the trained defect detection network model to obtain shallow texture features and high-level semantic features. The shallow texture features are transferred to the high-level semantic features through skip connection. The surface defect detection data under different detection operation modes are obtained at a terminal. This application also provides a surface defect detection system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.