Network training process for hardware definition
US11151447B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 13, 2017 |
| Grant date | Oct 19, 2021 |
| Priority date | — |
| Expiry date | Mar 8, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
This disclosure describes methods, apparatuses, and systems for network training and testing for evaluating hardware characteristics and for hardware selection. For example, a sensor can capture a dataset, which may be transformed into a plurality of modified datasets to simulate changes to hardware. Each of the plurality of modified datasets may be used to individually train an untrained neural network, thereby producing a plurality of trained neural networks. In order to evaluate the trained neural networks, each neural network can be used to ingest an evaluation dataset to perform a variety of tasks, such as identifying various objects within the dataset. A performance of each neural network can be determined and compared. A performance curve can be determined for each characteristic under review, facilitating a selection of one or more hardware components and/or configurations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.