Patents by Inventor Aloïs Peter Prieur De La Comble

Aloïs Peter Prieur De La Comble 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).

  • DIGITAL QUALITY CONTROL USING COMPUTER VISIONING WITH DEEP LEARNING
    Publication number: 20220292668
    Abstract: Implementations include receiving sample data, the sample data being generated as digital data representative of a sample of the product, providing a set of features by processing the sample data through multiple layers of a residual network, a first layer of the residual network identifying one or more features of the sample data, and a second layer of the residual network receiving the one or more features of the first layer, and identifying one or more additional features, processing the set of features using a CNN to identify a set of regions, and at least one object in a region of the set of regions, and determine a type of the at least one object, and selectively issuing an alert at least partially based on the type of the at least one object, the alert indicating contamination within the sample of the product.
    Type: Application
    Filed: May 27, 2022
    Publication date: September 15, 2022
    Inventors: Olivier Bonneau, Sami Hamani, Aloïs Peter Prieur De La Comble, Patrick Cottereau
  • Digital quality control using computer visioning with deep learning
    Patent number: 11373287
    Abstract: Implementations include receiving sample data, the sample data being generated as digital data representative of a sample of the product, providing a set of features by processing the sample data through multiple layers of a residual network, a first layer of the residual network identifying one or more features of the sample data, and a second layer of the residual network receiving the one or more features of the first layer, and identifying one or more additional features, processing the set of features using a CNN to identify a set of regions, and at least one object in a region of the set of regions, and determine a type of the at least one object, and selectively issuing an alert at least partially based on the type of the at least one object, the alert indicating contamination within the sample of the product.
    Type: Grant
    Filed: December 18, 2018
    Date of Patent: June 28, 2022
    Assignee: Accenture Global Solutions Limited
    Inventors: Olivier Bonneau, Sami Hamani, Aloïs Peter Prieur De La Comble, Patrick Cottereau
  • DIGITAL QUALITY CONTROL USING COMPUTER VISIONING WITH DEEP LEARNING
    Publication number: 20200082522
    Abstract: Implementations include receiving sample data, the sample data being generated as digital data representative of a sample of the product, providing a set of features by processing the sample data through multiple layers of a residual network, a first layer of the residual network identifying one or more features of the sample data, and a second layer of the residual network receiving the one or more features of the first layer, and identifying one or more additional features, processing the set of features using a CNN to identify a set of regions, and at least one object in a region of the set of regions, and determine a type of the at least one object, and selectively issuing an alert at least partially based on the type of the at least one object, the alert indicating contamination within the sample of the product.
    Type: Application
    Filed: December 18, 2018
    Publication date: March 12, 2020
    Inventors: Olivier Bonneau, Sami Hamani, Aloïs Peter Prieur De La Comble, Patrick Cottereau