Patents by Inventor Andrejs Sautins

Andrejs Sautins 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).

  • GENERATIVE AUGMENTATION OF IMAGE DATA
    Publication number: 20200334532
    Abstract: Systems and methods to receive one or more first images associated with a training set of images to train a machine learning model; provide the one or more first images as a first input to a first set of layers of computational units, wherein the first set of layers utilizes image filters; provide a first output of the first set of layers of computational units as a second input to a second layer of the computational units, wherein the second layer utilizes random parameter sets for computations; obtain distortion parameters from the second layer of the computational units; generate one or more second images comprising a representation of the one or more first images modified with the distortion parameters; obtain, as a third output, the one or more second images; and add the one or more second images to the training set of images to train the machine learning model.
    Type: Application
    Filed: June 1, 2020
    Publication date: October 22, 2020
    Inventors: Konstantin Zuev, Andrejs Sautins
  • Generative augmentation of image data
    Patent number: 10671920
    Abstract: Systems and methods to receive one or more first images associated with a training set of images to train a machine learning model; provide the one or more first images as a first input to a first set of layers of computational units, wherein the first set of layers utilizes image filters; provide a first output of the first set of layers of computational units as a second input to a second layer of the computational units, wherein the second layer utilizes random parameter sets for computations; obtain distortion parameters from the second layer of the computational units; generate one or more second images comprising a representation of the one or more first images modified with the distortion parameters; obtain, as a third output, the one or more second images; and add the one or more second images to the training set of images to train the machine learning model.
    Type: Grant
    Filed: March 28, 2018
    Date of Patent: June 2, 2020
    Assignee: ABBYY Production LLC
    Inventors: Konstantin Zuev, Andrejs Sautins
  • GENERATIVE AUGMENTATION OF IMAGE DATA
    Publication number: 20190294961
    Abstract: Systems and methods to receive one or more first images associated with a training set of images to train a machine learning model; provide the one or more first images as a first input to a first set of layers of computational units, wherein the first set of layers utilizes image filters; provide a first output of the first set of layers of computational units as a second input to a second layer of the computational units, wherein the second layer utilizes random parameter sets for computations; obtain distortion parameters from the second layer of the computational units; generate one or more second images comprising a representation of the one or more first images modified with the distortion parameters; obtain, as a third output, the one or more second images; and add the one or more second images to the training set of images to train the machine learning model.
    Type: Application
    Filed: March 28, 2018
    Publication date: September 26, 2019
    Inventors: Konstantin Zuev, Andrejs Sautins