Patents by Inventor Eli Passov

Eli Passov 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: 12260319
    Abstract: An integrated circuit with arrays of convolution units that include hardware convolution neural network units configured to perform efficient expansion process by parallelization. The integrated circuit includes multiple building blocks that include the arrays of convolution units, inputs, and outputs t.
    Type: Grant
    Filed: April 8, 2021
    Date of Patent: March 25, 2025
    Assignee: AUTOBRAINS TECHNOLOGIES LTD
    Inventor: Eli Passov
  • Patent number: 12205015
    Abstract: An apparatus that may include a neural network processor, the neural network processor comprises multiple building blocks. Each of the at least some of the building blocks may include, may consist or may consist essentially of a channel split unit, a convolution unit, a concatenation unit, and a shuffle unit.
    Type: Grant
    Filed: April 8, 2021
    Date of Patent: January 21, 2025
    Assignee: AUTOBRAINS TECHNOLOGIES LTD.
    Inventor: Eli Passov
  • Patent number: 11755920
    Abstract: A method that may include training a student ODNN to mimic a teacher ODNN. The training may include calculating a teacher student detection loss that is based on a pre-bounding-box output of the teacher ODNN. The pre-bounding-box output of the teacher ODNN is a function of pre-bounding-box outputs of different ODNNs that belong to the teacher ODNN. The method may also include detecting one or more objects in an image, by feeding the image to the trained student ODNN; outputting by the trained student ODNN a student pre-bounding-box output; and calculating one or more bounding boxes based on the student pre-bounding-box output.
    Type: Grant
    Filed: March 4, 2020
    Date of Patent: September 12, 2023
    Assignee: CORTICA LTD.
    Inventors: Igal Raichelgauz, Eli Passov
  • Patent number: 11694088
    Abstract: A method that may include training a student ODNN to mimic a teacher ODNN. The training may include calculating a teacher student detection loss that is based on a pre-bounding-box output of the teacher ODNN. The pre-bounding-box output of the teacher ODNN is a function of pre-bounding-box outputs of different ODNNs that belong to the teacher ODNN. The method may also include detecting one or more objects in an image, by feeding the image to the trained student ODNN; outputting by the trained student ODNN a student pre-bounding-box output; and calculating one or more bounding boxes based on the student pre-bounding-box output.
    Type: Grant
    Filed: February 5, 2020
    Date of Patent: July 4, 2023
    Assignee: CORTICA LTD.
    Inventors: Igal Raichelgauz, Eli Passov
  • Publication number: 20210319297
    Abstract: An apparatus that may include a neural network processor, the neural network processor comprises multiple building blocks. Each of the at least some of the building blocks may include, may consist or may consist essentially of an input, an output and at least one array convolution unit.
    Type: Application
    Filed: April 8, 2021
    Publication date: October 14, 2021
    Applicant: AUTOBRAINS TECHNOLOGIES LTD
    Inventor: Eli Passov
  • Publication number: 20210319296
    Abstract: An apparatus that may include a neural network processor, the neural network processor comprises multiple building blocks. Each of the at least some of the building blocks may include, may consist or may consist essentially of a channel split unit, a convolution unit, a concatenation unit, and a shuffle unit.
    Type: Application
    Filed: April 8, 2021
    Publication date: October 14, 2021
    Applicant: AUTOBRAINS TECHNOLOGIES LTD.
    Inventor: Eli Passov
  • Publication number: 20200293903
    Abstract: A method that may include training a student ODNN to mimic a teacher ODNN. The training may include calculating a teacher student detection loss that is based on a pre-bounding-box output of the teacher ODNN. The pre-bounding-box output of the teacher ODNN is a function of pre-bounding-box outputs of different ODNNs that belong to the teacher ODNN. The method may also include detecting one or more objects in an image, by feeding the image to the trained student ODNN; outputting by the trained student ODNN a student pre-bounding-box output; and calculating one or more bounding boxes based on the student pre-bounding-box output.
    Type: Application
    Filed: February 5, 2020
    Publication date: September 17, 2020
    Applicant: Cortica Ltd.
    Inventors: Igal Raichelgauz, Eli Passov
  • Publication number: 20200293904
    Abstract: A method that may include training a student ODNN to mimic a teacher ODNN. The training may include calculating a teacher student detection loss that is based on a pre-bounding-box output of the teacher ODNN. The pre-bounding-box output of the teacher ODNN is a function of pre-bounding-box outputs of different ODNNs that belong to the teacher ODNN. The method may also include detecting one or more objects in an image, by feeding the image to the trained student ODNN; outputting by the trained student ODNN a student pre-bounding-box output; and calculating one or more bounding boxes based on the student pre-bounding-box output.
    Type: Application
    Filed: March 4, 2020
    Publication date: September 17, 2020
    Applicant: CORTICA LTD.
    Inventors: Igal Raichelgauz, Eli Passov