Stacked neural network framework in the internet of things
US10902302B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 23, 2018 |
| Grant date | Jan 26, 2021 |
| Priority date | — |
| Expiry date | Aug 31, 2038 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY04S40/18
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for dividing, by a training system, a computational training work load of one or more neural network layers; pre-training the one or more neural network layers with a first class of image data sensitive to an original known dataset; generating a first weight file from the first layer of the neural network based on the first class of image data sensitive to the original known dataset; loading the one or more pre-trained neural network layers and the generated first weight file into at least one Internet of Things (IoT) device; stacking the one or more pre-trained neural network layers with the first layer of the neural network to form a new training system for an uploaded new dataset; adjusting the generated first weight file based on an input of one or more new classes of image data comprised in the uploaded new dataset to generate a new second weight file; inferencing an object class of new image data comprised on the uploaded new dataset using the generated new second weight file; and outputting the inferenced object class of the new image data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.