Invention Grant
- Patent Title: Broad area geospatial object detection using autogenerated deep learning models
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Application No.: US16553060Application Date: 2019-08-27
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Publication No.: US10733759B2Publication Date: 2020-08-04
- Inventor: Adam Estrada , Andrew Jenkins , Benjamin Brock , Chris Mangold
- Applicant: DigitalGlobe, Inc.
- Applicant Address: US CO Westminster
- Assignee: DIGITALGLOBE, INC.
- Current Assignee: DIGITALGLOBE, INC.
- Current Assignee Address: US CO Westminster
- Agency: Galvin Patent Law LLC
- Agent Brian R. Galvin
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/73 ; G06T5/00 ; G06K9/46 ; G06K9/00 ; G06T7/33

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.
Public/Granted literature
- US20200118292A1 BROAD AREA GEOSPATIAL OBJECT DETECTION USING AUTOGENERATED DEEP LEARNING MODELS Public/Granted day:2020-04-16
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