Patents by Inventor Alexander Daniel Friedman

Alexander Daniel Friedman 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: 11023791
    Abstract: An example system includes a processor and a non-transitory computer-readable medium having stored therein instructions that are executable to cause the system to perform various functions. The functions include obtaining a source profile associated with a print job and a destination profile associated with the print job. The functions also include, based on the source profile and the destination profile, generating a color conversion object that maps input colors of a source color space to output colors of a destination color space. In addition, the functions include training a neural network using the color conversion object so as to obtain weights associated with two or more hidden layers of nodes of the neural network. Further, the functions include receiving color data corresponding to pixels of the print job, and converting the color data from the source color space to the destination color space using the neural network.
    Type: Grant
    Filed: October 30, 2019
    Date of Patent: June 1, 2021
    Assignee: KYOCERA Document Solutions Inc.
    Inventors: Michael M. Chang, Alexander Daniel Friedman
  • Publication number: 20210133522
    Abstract: An example system includes a processor and a non-transitory computer-readable medium having stored therein instructions that are executable to cause the system to perform various functions. The functions include obtaining a source profile associated with a print job and a destination profile associated with the print job. The functions also include, based on the source profile and the destination profile, generating a color conversion object that maps input colors of a source color space to output colors of a destination color space. In addition, the functions include training a neural network using the color conversion object so as to obtain weights associated with two or more hidden layers of nodes of the neural network. Further, the functions include receiving color data corresponding to pixels of the print job, and converting the color data from the source color space to the destination color space using the neural network.
    Type: Application
    Filed: October 30, 2019
    Publication date: May 6, 2021
    Inventors: Michael M. Chang, Alexander Daniel Friedman