Patents by Inventor Ebot Etchu Ndip-Agbor

Ebot Etchu Ndip-Agbor 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).

  • Publication number: 20230343058
    Abstract: In various embodiments, a training application trains a machine learning model to modify portions of shapes when designing 3D objects. The training application converts first structural analysis data having a first resolution to first coarse structural analysis data having a second resolution that is lower than the first resolution. Subsequently, the training application generates one or more training sets based on a first shape, the first coarse structural analysis data, and a second shape that is derived from the first shape. Each training set is associated with a different portion of the first shape. The training application then performs one or more machine learning operations on the machine learning model using the training set(s) to generate a trained machine learning model. The trained machine learning model modifies at least a portion of a shape having the first resolution based on coarse structural analysis data having the second resolution.
    Type: Application
    Filed: July 3, 2023
    Publication date: October 26, 2023
    Inventors: Ran ZHANG, Morgan FABIAN, Ebot Etchu NDIP-AGBOR, Lee Morris TAYLOR
  • Patent number: 11694415
    Abstract: In various embodiments, a training application trains a machine learning model to modify portions of shapes when designing 3D objects. The training application converts first structural analysis data having a first resolution to first coarse structural analysis data having a second resolution that is lower than the first resolution. Subsequently, the training application generates one or more training sets based on a first shape, the first coarse structural analysis data, and a second shape that is derived from the first shape. Each training set is associated with a different portion of the first shape. The training application then performs one or more machine learning operations on the machine learning model using the training set(s) to generate a trained machine learning model. The trained machine learning model modifies at least a portion of a shape having the first resolution based on coarse structural analysis data having the second resolution.
    Type: Grant
    Filed: October 28, 2020
    Date of Patent: July 4, 2023
    Assignee: AUTODESK, INC.
    Inventors: Ran Zhang, Morgan Fabian, Ebot Etchu Ndip-Agbor, Lee Morris Taylor
  • Publication number: 20230152778
    Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using techniques that facilitate manufacturing, include: modifying a three dimensional shape, for which a corresponding physical structure is to be created using a manufacturing process, to produce a modified three dimensional shape; and providing the modified shape of the modeled object for use in manufacturing the physical structure using one or more computer-controlled manufacturing systems that employ the manufacturing process.
    Type: Application
    Filed: November 1, 2022
    Publication date: May 18, 2023
    Inventors: Benjamin McKittrick Weiss, Jesus Rodriguez, Ebot Etchu Ndip-Agbor, Nigel Jed Wesley Morris, Adrian Adam Thomas Butscher