Broad area geospatial object detection using autogenerated deep learning models
US10395388B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 3, 2018 |
| Grant date | Aug 27, 2019 |
| Priority date | — |
| Expiry date | Jul 3, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30252
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system for automated geospatial image analysis comprising a deep learning model that receives orthorectified geospatial images, pre-labeled to demarcate objects of interest. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to a convolutional neural network. This process may be repeated so that an image analysis software module can detect multiple object types or categories. The image analysis software module receives orthorectified geospatial images from one or more geospatial image caches. Using a multi-scale sliding window submodule, image analysis software scans geospatial images, detects objects present and geospatially locates them.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.