Patents by Inventor Hamid Behroozi

Hamid Behroozi 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: 11308598
    Abstract: A method for quality assessment of an image. The method includes generating an (i+1)th plurality of feature maps from an image, obtaining an (i+1)th feature set of a plurality of feature sets from the (i+1)th plurality of feature maps, and extracting a score distribution for a plurality of scores from the plurality of feature sets. The plurality of scores are associated with the image. The score distribution is extracted by feeding the plurality of feature sets to a first (1st) fully connected layer of a plurality of fully connected layers. The plurality of fully connected layers are associated with a convolutional neural network.
    Type: Grant
    Filed: February 14, 2020
    Date of Patent: April 19, 2022
    Assignee: SHARIF UNIVERSITY OF TECHNOLOGY
    Inventors: Hatef Otroshi Shahreza, Arash Amini, Hamid Behroozi
  • Publication number: 20220076041
    Abstract: A method for quality assessment of digital media. The method includes dividing the digital media to a plurality of frame subsets, generating a plurality of frame-level feature sets by generating an mth frame-level feature set, and extracting a score distribution for a plurality of scores from the plurality of frame-level feature sets. Each of the plurality of frame subsets includes a plurality of frames. The mth frame-level feature set is associated with an mth frame subset of the plurality of frame subsets where m?[1, M] and M is a number of the plurality of frame subsets. The mth frame-level feature set includes a plurality of feature sets. The score distribution is associated with the digital media.
    Type: Application
    Filed: November 15, 2021
    Publication date: March 10, 2022
    Applicant: Sharif University of Technology
    Inventors: Hatef Otroshi Shahreza, Arash Amini, Hamid Behroozi
  • Patent number: 11176654
    Abstract: A method for quality assessment of a video that includes M video frames. The method includes repeating a first iterative process M times and extracting a score distribution for a plurality of scores. An mth iteration of the first iterative process, where m ? [1,M], includes generating an mth frame-level feature set, generating a first recurrent output of a plurality of recurrent outputs based on a zeroth recurrent output of the plurality of recurrent outputs, and generating an mth recurrent output of the plurality of recurrent outputs based on an (m?1)th recurrent output of the plurality of recurrent outputs. The first recurrent output is generated by feeding a first frame-level feature set to a recurrent neural network. The mth recurrent output is generated by feeding the mth frame-level feature set to the recurrent neural network. The score distribution is extracted from an Mth recurrent output of the plurality of recurrent outputs.
    Type: Grant
    Filed: March 26, 2020
    Date of Patent: November 16, 2021
    Assignee: SHARIF UNIVERSITY OF TECHNOLOGY
    Inventors: Hatef Otroshi Shahreza, Arash Amini, Hamid Behroozi
  • Publication number: 20200226740
    Abstract: A method for quality assessment of a video that includes M video frames. The method includes repeating a first iterative process M times and extracting a score distribution for a plurality of scores. An mth iteration of the first iterative process, where m ? [1,M], includes generating an mth frame-level feature set, generating a first recurrent output of a plurality of recurrent outputs based on a zeroth recurrent output of the plurality of recurrent outputs, and generating an mth recurrent output of the plurality of recurrent outputs based on an (m?1)th recurrent output of the plurality of recurrent outputs. The first recurrent output is generated by feeding a first frame-level feature set to a recurrent neural network. The mth recurrent output is generated by feeding the mth frame-level feature set to the recurrent neural network. The score distribution is extracted from an Mth recurrent output of the plurality of recurrent outputs.
    Type: Application
    Filed: March 26, 2020
    Publication date: July 16, 2020
    Applicant: Sharif University of Technology
    Inventors: Hatef Otroshi Shahreza, Arash Amini, Hamid Behroozi
  • Publication number: 20200184627
    Abstract: A method for quality assessment of an image. The method includes generating an (i+1)th plurality of feature maps from an image, obtaining an (i+1)th feature set of a plurality of feature sets from the (i+1)th plurality of feature maps, and extracting a score distribution for a plurality of scores from the plurality of feature sets. The plurality of scores are associated with the image. The score distribution is extracted by feeding the plurality of feature sets to a first (1st) fully connected layer of a plurality of fully connected layers. The plurality of fully connected layers are associated with a convolutional neural network.
    Type: Application
    Filed: February 14, 2020
    Publication date: June 11, 2020
    Applicant: Sharif University of Technology
    Inventors: Hatef Otroshi Shahreza, Arash Amini, Hamid Behroozi