Systems and methods for optimized computer vision using deep neural networks and Litpschitz analysis
US10839253B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 17, 2019 |
| Grant date | Nov 17, 2020 |
| Priority date | — |
| Expiry date | Jun 17, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/82
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Computer vision systems and methods for optimized computer vision using deep neural networks and Lipschitz analysis are provided. The system receives signals or data related to visual imagery, such as data from a camera, and feed-forwards the signals/data through the multiple layers of a convolutional neural network (CNN). At one or more layers of the CNN, the system determines at least one Bessel bound of that layer. The system then determines a Lipschitz bound based on the one or more Bessel bounds. The system then applies the Lipschitz bound to the signals. Once the Lipschitz bound is applied, the system can feed-forward the signals to other processes of the layer or to a further layer.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.