Patents by Inventor Yaaqov VALERO

Yaaqov VALERO 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: 11436849
    Abstract: Provided herein are systems and methods for applying adaptive classes thresholds to enhance object detection Machine Learning (ML) models by receiving a plurality of labeled feature vectors extracted from a plurality of images associated with a plurality of objects, one or more subsets of the plurality of feature vectors are associated with respective object(s) and labeled accordingly, computing an adaptive threshold for each object in a plurality of iterations, each iteration comprising: (1) computing deviation of a respective feature vector of the subset from an aggregated feature vector, (2) computing, in case the deviation is within a predefined value, a threshold enclosing the respective feature vector, and (3) adjusting the adaptive threshold to enclose the threshold of the respective feature vector and outputting the adaptive threshold(s) for classifying unlabeled feature vectors to class(s) of respective object(s) associated with the adaptive threshold(s) in which the unlabeled feature vectors fall.
    Type: Grant
    Filed: July 20, 2020
    Date of Patent: September 6, 2022
    Assignee: Anyvision Interactive Technologies Ltd.
    Inventors: Alexander Zilberman, Ailon Etshtein, Neil Martin Robertson, Sankha Subhra Mukherjee, Rolf Hugh Baxter, Ishay Sivan, Yaaqov Valero
  • Publication number: 20210034929
    Abstract: Provided herein are systems and methods for applying adaptive classes thresholds to enhance object detection Machine Learning (ML) models by receiving a plurality of labeled feature vectors extracted from a plurality of images associated with a plurality of objects, one or more subsets of the plurality of feature vectors are associated with respective object(s) and labeled accordingly, computing an adaptive threshold for each object in a plurality of iterations, each iteration comprising: (1) computing deviation of a respective feature vector of the subset from an aggregated feature vector, (2) computing, in case the deviation is within a predefined value, a threshold enclosing the respective feature vector, and (3) adjusting the adaptive threshold to enclose the threshold of the respective feature vector and outputting the adaptive threshold(s) for classifying unlabeled feature vectors to class(s) of respective object(s) associated with the adaptive threshold(s) in which the unlabeled feature vectors fall.
    Type: Application
    Filed: July 20, 2020
    Publication date: February 4, 2021
    Applicant: Anyvision Interactive Technologies Ltd.
    Inventors: Alexander ZILBERMAN, Ailon ETSHTEIN, Neil Martin ROBERTSON, Sankha Subhra MUKHERJEE, Rolf Hugh BAXTER, Ishay SIVAN, Yaaqov VALERO