Patents by Inventor Christopher Burd

Christopher Burd has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10636169
    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.
    Type: Grant
    Filed: December 18, 2018
    Date of Patent: April 28, 2020
    Assignee: DIGITALGLOBE, INC.
    Inventors: Adam Estrada, Christopher Burd, Andrew Jenkins, Joseph Newbrough, Scott Szoko, Melanie Vinton
  • Publication number: 20190385338
    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.
    Type: Application
    Filed: December 18, 2018
    Publication date: December 19, 2019
    Inventors: Adam Estrada, Christopher Burd, Andrew Jenkins, Joseph Newbrough, Scott Szoko, Melanie Vinton
  • Patent number: 10157479
    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.
    Type: Grant
    Filed: September 19, 2017
    Date of Patent: December 18, 2018
    Assignee: DigitalGlobe, Inc.
    Inventors: Adam Estrada, Christopher Burd, Andrew Jenkins, Joseph Newbrough, Scott Szoko, Melanie Vinton
  • Publication number: 20180158210
    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.
    Type: Application
    Filed: September 19, 2017
    Publication date: June 7, 2018
    Inventors: Adam Estrada, Christopher Burd, Andrew Jenkins, Joseph Newbrough, Scott Szoko, Melanie Vinton
  • Patent number: 9767565
    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.
    Type: Grant
    Filed: June 27, 2016
    Date of Patent: September 19, 2017
    Assignee: DigitalGlobe, Inc.
    Inventors: Adam Estrada, Christopher Burd, Andrew Jenkins, Joseph Newbrough, Scott Szoko, Melanie Vinton
  • Publication number: 20170061625
    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.
    Type: Application
    Filed: June 27, 2016
    Publication date: March 2, 2017
    Inventors: Adam Estrada, Christopher Burd, Andrew Jenkins, Joseph Newbrough, Scott Szoko, Melanie Vinton