Systems and methods for optical material characterization of waste materials using machine learning
US11069053B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2018 |
| Grant date | Jul 20, 2021 |
| Priority date | — |
| Expiry date | May 28, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/52
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for optical material characterization of waste materials using machine learning are provided. In one embodiment, a system comprises: an imaging device configured to generate image frames an area and target objects within the area; an object characterization processor coupled to the imaging device and comprising Neural Processing Units and a Neural Network Parameter Set. The Neural Network Parameter Set stores learned parameters utilized by the one or more Neural Processing Units for characterizing the one or more target objects. The Neural Processing Units are configured by the Neural Network Parameter Set to detect a presence of a plurality of different materials within the image frames based on a plurality of different features. For a first image frame of the plurality of image frames, the Neural Processing Units outputs material characterization data that identifies which of the plurality of different materials are detected in the first image frame.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.