Deep learning image processing method for determining vehicle damage
US10762385B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 29, 2018 |
| Grant date | Sep 1, 2020 |
| Priority date | — |
| Expiry date | Feb 5, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In a computer-implemented method and associated tangible non-transitory computer-readable medium, an image of a damaged vehicle may be analyzed to generate a repair estimate. A dataset populated with digital images of damaged vehicles and associated claim data may be used to train a deep learning neural network to learn damaged vehicle image characteristics that are predictive of claim data characteristics, and a predictive similarity model may be generated. Using the predictive similarity model, one or more similarity scores may be generated for a digital image of a newly damaged vehicle, indicating its similarity to one or more digital images of damaged vehicles with known damage level, repair time, and/or repair cost. A repair estimate may be generated for the newly damaged vehicle based on the claim data associated with images that are most similar to the image of the newly damaged vehicle.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.