Object detection using recurrent neural network and concatenated feature map
US10198655B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 24, 2017 |
| Grant date | Feb 5, 2019 |
| Priority date | — |
| Expiry date | Jan 24, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/10004
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
According to one embodiment, a system includes a sensor component and a detection component. The sensor component is configured to obtain a first stream of sensor data and a second stream of sensor data, wherein each of the first stream and second stream comprise a plurality of sensor frames. The detection component is configured to generate a concatenated feature map based on a sensor frame of a first type and a sensor frame of a second type. The detection component is configured to detect one or more objects based on the concatenated feature map. One or more of generating and detecting comprises generating or detecting using a neural network with a recurrent connection that feeds information about features or objects from previous frames.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.