Patents by Inventor Steve Cruz

Steve Cruz 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).

  • Machine learning systems and methods for improved localization of image forgery
    Patent number: 11663489
    Abstract: A system for improved localization of image forgery. The system generates a variational information bottleneck objective function and works with input image patches to implement an encoder-decoder architecture. The encoder-decoder architecture controls an information flow between the input image patches and a representation layer. The system utilizes information bottleneck to learn useful residual noise patterns and ignore semantic content present in each input image patch. The system trains a neural network to learn a representation indicative of a statistical fingerprint of a source camera model from each input image patch while excluding semantic content thereof. The system can determine a splicing manipulation localization by the trained neural network.
    Type: Grant
    Filed: June 24, 2020
    Date of Patent: May 30, 2023
    Assignees: Insurance Services Office, Inc., The Regents of the University of Colorado
    Inventors: Aurobrata Ghosh, Steve Cruz, Terrance E. Boult, Maneesh Kumar Singh, Venkata Subbarao Veeravarasapu, Zheng Zhong
  • Machine Learning Systems and Methods for Improved Localization of Image Forgery
    Publication number: 20200402223
    Abstract: A system for improved localization of image forgery. The system generates a variational information bottleneck objective function and works with input image patches to implement an encoder-decoder architecture. The encoder-decoder architecture controls an information flow between the input image patches and a representation layer. The system utilizes information bottleneck to learn useful residual noise patterns and ignore semantic content present in each input image patch. The system trains a neural network to learn a representation indicative of a statistical fingerprint of a source camera model from each input image patch while excluding semantic content thereof. The system can determine a splicing manipulation localization by the trained neural network.
    Type: Application
    Filed: June 24, 2020
    Publication date: December 24, 2020
    Applicant: Insurance Services Office, Inc.
    Inventors: Aurobrata Ghosh, Steve Cruz, Terrance E. Boult, Maneesh Kumar Singh, Venkata Subbarao Veeravarasapu, Zheng Zhong