Training and/or using neural network models to generate intermediary output of a spectral image
US10331975B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Nov 29, 2016 |
| Grant date | Jun 25, 2019 |
| Priority date | — |
| Expiry date | Nov 29, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems, methods, and computer readable media related to training and/or using a neural network model. The trained neural network model can be utilized to generate (e.g., over a hidden layer) a spectral image based on a regular image, and to generate output indicative of one or more features present in the generated spectral image (and present in the regular image since the spectral image is generated based on the regular image). As one example, a regular image may be applied as input to the trained neural network model, a spectral image generated over multiple layers of the trained neural network model based on the regular image, and output generated over a plurality of additional layers based on the spectral image. The generated output may be indicative of various features, depending on the training of the additional layers of the trained neural network model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.