Patents by Inventor Anouar MELLAKH

Anouar MELLAKH 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).

  • Methods for learning the parameters of a convolutional neural network, and for classifying an input datum
    Patent number: 11790222
    Abstract: The present invention concerns a method for learning the parameters of a convolutional neural network, CNN, for data classification, the method comprising the implementation of steps by data processing means (11a, 11 b, 11c) of at least one server (1a, 1b, 1c), of: (a1) Learning, from a base of already-classified confidential learning data, the parameters of a first CNN; (a2) Learning, from a base of already-classified public learning data, the parameters of a last fully-connected layer (FC) of a second CNN corresponding to the first CNN to which said fully-connected layer (FC) has been added. The present invention also concerns a method for classifying an input datum.
    Type: Grant
    Filed: March 18, 2019
    Date of Patent: October 17, 2023
    Assignee: IDEMIA IDENTITY & SECURITY FRANCE
    Inventors: Herve Chabanne, Vincent Despiegel, Anouar Mellakh
  • Methods for learning parameters of a convolutional neural network, and classifying an input datum
    Patent number: 11574180
    Abstract: The present invention relates to a method for learning parameters of a convolutional neural network, CNN, for data classification, the method comprising the implementation, by means for processing data (11) of a server (1), of steps consisting of: (a1) Learning, from an already classified learning database, the parameters of a CNN, called quantized CNN, such that said parameters are valued in a discrete space; (a2) Generating a white-box implementation of at least one layer of said quantized CNN, said white-box implementation being predetermined based on at least one of said learned parameters. The present invention also relates to a method for classifying an input datum.
    Type: Grant
    Filed: January 15, 2019
    Date of Patent: February 7, 2023
    Assignee: IDEMIA IDENTITY & SECURITY FRANCE
    Inventors: Herve Chabanne, Vincent Despiegel, Anouar Mellakh
  • METHODS FOR LEARNING THE PARAMETERS OF A CONVOLUTIONAL NEURAL NETWORK, AND FOR CLASSIFYING AN INPUT DATUM
    Publication number: 20190294864
    Abstract: The present invention concerns a method for learning the parameters of a convolutional neural network, CNN, for data classification, the method comprising the implementation of steps by data processing means (11a, 11 b, 11c) of at least one server (1a, 1b, 1c), of: (a1) Learning, from a base of already-classified confidential learning data, the parameters of a first CNN; (a2) Learning, from a base of already-classified public learning data, the parameters of a last fully-connected layer (FC) of a second CNN corresponding to the first CNN to which said fully-connected layer (FC) has been added. The present invention also concerns a method for classifying an input datum.
    Type: Application
    Filed: March 18, 2019
    Publication date: September 26, 2019
    Inventors: Herve CHABANNE, Vincent DESPIEGEL, Anouar MELLAKH
  • METHODS FOR LEARNING PARAMETERS OF A CONVOLUTIONAL NEURAL NETWORK, AND CLASSIFYING AN INPUT DATUM
    Publication number: 20190220743
    Abstract: The present invention relates to a method for learning parameters of a convolutional neural network, CNN, for data classification, the method comprising the implementation, by means for processing data (11) of a server (1), of steps consisting of: (a1) Learning, from an already classified learning database, the parameters of a CNN, called quantized CNN, such that said parameters are valued in a discrete space; (a2) Generating a white-box implementation of at least one layer of said quantized CNN, said white-box implementation being predetermined based on at least one of said learned parameters. The present invention also relates to a method for classifying an input datum.
    Type: Application
    Filed: January 15, 2019
    Publication date: July 18, 2019
    Inventors: Herve CHABANNE, Vincent DESPIEGEL, Anouar MELLAKH