Patents by Inventor Michael Ferdman

Michael Ferdman 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).

  • Publication number: 20210141524
    Abstract: A system for creating programs with gestures with a touch computer having a touch display, a plurality of actions preloaded on the touch computer for execution by the touch computer when triggered, a trigger received by the touch computer, software executing on the touch computer for associating the trigger with a corresponding one of the plurality of actions, text received by the software, text combinable with the triggers by the software into a program, a plurality of elements and operations components available to the touch computer for inclusion in the program, software executing on the touch computer for displaying a menu with a section for associating a gesture received by the touch display with a property of at least one element, wherein the gesture is a horizontal movement of the section relative to the touch display, a central computer in communication with the touch computer, and the central computer connected to the Internet to make the program available to authorized users.
    Type: Application
    Filed: November 8, 2019
    Publication date: May 13, 2021
    Inventors: Joon Park, Daniel LaCivita, Michael Ferdman, Eric Eng
  • Patent number: 10726330
    Abstract: System, method, and accelerator to process a convolutional neural network. In accordance therewith, a tile structure having input data values is loaded for a convolution layer. Each tile of the tile structure corresponds to a respective feature map in a set of input feature maps. The tile structure of each iteration represents a different subset of data values in the input feature maps. Intermediate data values associated with a subset of the data values of the input feature maps in the current intermediate tile structure are reused, when the intermediate data values of a previous tile structure overlap values to be computed in the current tile structure. Intermediate non-overlapping data values that are associated with the subset of the data values in the current tile structure are computed using associated filters having weight data values. Available reused intermediate data values and computed intermediate data values are buffered as intermediate data.
    Type: Grant
    Filed: October 11, 2017
    Date of Patent: July 28, 2020
    Assignee: The Research Foundation for The State University of New York
    Inventors: Michael Ferdman, Peter Milder, Manoj Alwani
  • Publication number: 20190220734
    Abstract: System, method, and accelerator to process a convolutional neural network. In accordance therewith, a tile structure having input data values is loaded for a convolution layer. Each tile of the tile structure corresponds to a respective feature map in a set of input feature maps. The tile structure of each iteration represents a different subset of data values in the input feature maps. Intermediate data values associated with a subset of the data values of the input feature maps in the current intermediate tile structure are reused, when the intermediate data values of a previous tile structure overlap values to be computed in the current tile structure. Intermediate non-overlapping data values that are associated with the subset of the data values in the current tile structure are computed using associated filters having weight data values. Available reused intermediate data values and computed intermediate data values are buffered as intermediate data.
    Type: Application
    Filed: October 11, 2017
    Publication date: July 18, 2019
    Inventors: Michael Ferdman, Peter Milder, Manoj Alwani