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1. (WO2017151673) SYNTHESIZING TRAINING DATA FOR BROAD AREA GEOSPATIAL OBJECT DETECTION

Pub. No.:    WO/2017/151673    International Application No.:    PCT/US2017/020032
Publication Date: Sat Sep 09 01:59:59 CEST 2017 International Filing Date: Wed Mar 01 00:59:59 CET 2017
IPC: G06K 9/62
G06T 3/00
Applicants: DIGITALGLOBE, INC.
Inventors: ESTRADA, Adam
JENKINS, Andrew
BURD, Christopher
NEWBROUGH, Joseph
SZOKO, Scott
VINTON, Melanie
Title: SYNTHESIZING TRAINING DATA FOR BROAD AREA GEOSPATIAL OBJECT DETECTION
Abstract:
A system for broad area geospatial object recognition, identification, classification, location and quantification, comprising an image manipulation module to create synthetically-generated images to imitate and augment an existing quantity of orthorectified geospatial images; together with a deep learning module and a convolutional neural network serving as an image analysis module, to analyze a large corpus of orthorectified geospatial images, identify and demarcate a searched object of interest from within the corpus, locate and quantify the identified or classified objects from the corpus of geospatial imagery available to the system. The system reports results in a requestor's preferred format.