Patents by Inventor Brett N. Appleton

Brett N. Appleton 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).

  • Synthetic-to-realistic image conversion using generative adversarial network (GAN) or other machine learning model
    Patent number: 12586359
    Abstract: A method includes obtaining training data having first image pairs, where each of the first image pairs includes (i) a first training image and (ii) a first ground truth image. The method also includes training a machine learning model to generate realistic images using the first image pairs. The method further includes obtaining additional training data having second image pairs, where each of the second image pairs includes (i) a second training image and (ii) a second ground truth image. At least some of the images in the second image pairs are less aligned or of lower quality than at least some of the images in the first image pairs. In addition, the method includes continuing to train the machine learning model to generate the realistic images using the second image pairs.
    Type: Grant
    Filed: June 23, 2023
    Date of Patent: March 24, 2026
    Assignee: Raytheon Company
    Inventors: Jonathan H. Goldstein, Lauren E. Turney, Richard W. Ely, Jody D. Verret, Brett N. Appleton
  • 3D FEATURE PROVENANCE FOR TARGETING, EXPLOITATION, OR OTHER FUNCTIONS
    Publication number: 20260045102
    Abstract: A method includes obtaining three-dimensional (3D) features associated with a scene, where each 3D feature is extracted based on two or more of multiple images of the scene. The method also includes identifying provenance data associated with each of the 3D features, where the provenance data for each 3D feature identifies one or more sources of the two or more images used to extract the 3D feature. The method further includes storing the 3D features and the provenance data associated with the 3D features.
    Type: Application
    Filed: April 8, 2025
    Publication date: February 12, 2026
    Inventors: Stephen Raif, Jody D. Verret, Kathryn A. Welin, Jennifer M. Swenson, Brett N. Appleton
  • SYNTHETIC-TO-REALISTIC IMAGE CONVERSION USING GENERATIVE ADVERSARIAL NETWORK (GAN) OR OTHER MACHINE LEARNING MODEL
    Publication number: 20240428568
    Abstract: A method includes obtaining training data having first image pairs, where each of the first image pairs includes (i) a first training image and (ii) a first ground truth image. The method also includes training a machine learning model to generate realistic images using the first image pairs. The method further includes obtaining additional training data having second image pairs, where each of the second image pairs includes (i) a second training image and (ii) a second ground truth image. At least some of the images in the second image pairs are less aligned or of lower quality than at least some of the images in the first image pairs. In addition, the method includes continuing to train the machine learning model to generate the realistic images using the second image pairs.
    Type: Application
    Filed: June 23, 2023
    Publication date: December 26, 2024
    Inventors: Jonathan H. Goldstein, Lauren E. Turney, Richard W. Ely, Jody D. Verret, Brett N. Appleton