Deep learning coordinate prediction using satellite and service data
US10699398B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 28, 2018 |
| Grant date | Jun 30, 2020 |
| Priority date | — |
| Expiry date | Jul 12, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/10032
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods of deep learning coordinate prediction using satellite and service data are disclosed herein. In some example embodiments, for each one of a plurality of places, a computer system trains a deep learning model based on training data of the plurality of places. The deep leaning model is configured to generate a predicted geographical location of a place based on satellite image data and service data associated with the place. The training data for each place comprises satellite image data of the place, service data, and a ground truth geographical location of the place. The service data comprises at least one of pick-up data indicating a geographical location at which a provider started transporting a requester in servicing a request associated with the place or drop-off data indicating a geographical location at which the provider completed transporting the requester in servicing the request associated with the place.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.