Parameter training method for a convolutional neural network and method for detecting items of interest visible in an image
US11138474B2 · kind B2 · utility
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Key dates
| Filing date | Oct 2, 2019 |
| Grant date | Oct 5, 2021 |
| Priority date | — |
| Expiry date | Jan 16, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A parameter training method for a convolutional neural network, CNN, for detecting items of interest visible in images by a data processor of at least one server. The method is implemented based on a plurality of training image databases. The items of interest are already annotated, the CNN being a CNN common to the plurality of training image databases and having a common core and a plurality of encoding layers, each one specific to one of the plurality of training image databases. The method is also for detecting items of interest visible in an image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.