Distracted driving detection using a multi-task training process
US11532169B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 15, 2021 |
| Grant date | Dec 20, 2022 |
| Priority date | — |
| Expiry date | Jul 3, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0499
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed are a multi-task training technique and resulting model for detecting distracted driving. In one embodiment, a method is disclosed comprising inputting a plurality of labeled examples into a multi-task network, the multi-task network comprising: a backbone network, the backbone network generating one or more feature vectors corresponding to each of the labeled examples, and a plurality of prediction heads coupled to the backbone network; minimizing a joint loss based on outputs of the plurality of prediction heads, the minimizing the joint loss causing a change in parameters of the backbone network; and storing a distraction classification model after minimizing the joint loss, the distraction classification model comprising the parameters of the backbone network and parameters of at least one of the prediction heads.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.