Patents by Inventor Shane A. Zabel

Shane A. Zabel 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).

  • Target identification in large image data
    Patent number: 11468266
    Abstract: A machine receives a large image having large image dimensions that exceed memory threshold dimensions. The large image includes metadata. The machine adjusts an orientation and a scaling of the large image based on the metadata. The machine divides the large image into a plurality of image tiles, each image tile having tile dimensions smaller than or equal to the memory threshold dimensions. The machine provides the plurality of image tiles to an artificial neural network. The machine identifies, using the artificial neural network, at least a portion of the target in at least one image tile. The machine identifies the target in the large image based on at least the portion of the target being identified in at least one image tile.
    Type: Grant
    Filed: September 27, 2019
    Date of Patent: October 11, 2022
    Assignee: Raytheon Company
    Inventors: Jonathan Goldstein, Stephen J. Raif, Philip A. Sallee, Jeffrey S. Klein, Steven A. Israel, Franklin Tanner, Shane A. Zabel, James Talamonti, Lisa A. Mccoy
  • Cross-modality automatic target recognition
    Patent number: 11373064
    Abstract: Discussed herein are systems, devices, and methods for automatic target recognition based on a non-visible input image. A method can include providing, as input to a first machine learning (ML) model for object classification, pixel data of a non-visible image, the first ML model including an encoder from a second ML model, the second ML model trained to generate a visible image representation of an input non-visible image, and receiving, from the first ML model, data indicating one or more objects present in the non-visible image.
    Type: Grant
    Filed: July 22, 2019
    Date of Patent: June 28, 2022
    Assignee: Raytheon Company
    Inventors: Jonathan Goldstein, Shane A. Zabel
  • TARGET IDENTIFICATION IN LARGE IMAGE DATA
    Publication number: 20210097344
    Abstract: A machine receives a large image having large image dimensions that exceed memory threshold dimensions. The large image includes metadata. The machine adjusts an orientation and a scaling of the large image based on the metadata. The machine divides the large image into a plurality of image tiles, each image tile having tile dimensions smaller than or equal to the memory threshold dimensions. The machine provides the plurality of image tiles to an artificial neural network. The machine identifies, using the artificial neural network, at least a portion of the target in at least one image tile. The machine identifies the target in the large image based on at least the portion of the target being identified in at least one image tile.
    Type: Application
    Filed: September 27, 2019
    Publication date: April 1, 2021
    Inventors: Jonathan Goldstein, Stephen J. Raif, Philip A. Sallee, Jeffrey S. Klein, Steven A. Israel, Franklin Tanner, Shane A. Zabel, James Talamonti, Lisa A. Mccoy
  • CROSS-MODALITY AUTOMATIC TARGET RECOGNITION
    Publication number: 20210027113
    Abstract: Discussed herein are systems, devices, and methods for automatic target recognition based on a non-visible input image. A method can include providing, as input to a first machine learning (ML) model for object classification, pixel data of a non-visible image, the first ML model including an encoder from a second ML model, the second ML model trained to generate a visible image representation of an input non-visible image, and receiving, from the first ML model, data indicating one or more objects present in the non-visible image.
    Type: Application
    Filed: July 22, 2019
    Publication date: January 28, 2021
    Inventors: Jonathan Goldstein, Shane A. Zabel