Sparse convolutional neural networks
US11061402B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 7, 2018 |
| Grant date | Jul 13, 2021 |
| Priority date | — |
| Expiry date | Aug 28, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05D1/249
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
The present disclosure provides systems and methods that apply neural networks such as, for example, convolutional neural networks, to sparse imagery in an improved manner. For example, the systems and methods of the present disclosure can be included in or otherwise leveraged by an autonomous vehicle. In one example, a computing system can extract one or more relevant portions from imagery, where the relevant portions are less than an entirety of the imagery. The computing system can provide the relevant portions of the imagery to a machine-learned convolutional neural network and receive at least one prediction from the machine-learned convolutional neural network based at least in part on the one or more relevant portions of the imagery. Thus, the computing system can skip performing convolutions over regions of the imagery where the imagery is sparse and/or regions of the imagery that are not relevant to the prediction being sought.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.