Patents by Inventor Weonsuk LEE

Weonsuk LEE 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).

  • METHOD FOR TRAINING NEURAL NETWORK AND DEVICE THEREOF
    Publication number: 20240062526
    Abstract: Provided is a method for training a neural network and a device thereof. The method for training a neural network with three-dimensional (3D) training image data comprising a plurality of two-dimensional (2D) training image data, comprises: training a first convolutional neural network (CNN) with the plurality of 2D training image data, wherein the first convolutional neural network comprises 2D convolutional layers; and training a second convolutional neural network with the 3D training image data, wherein the second convolutional neural network comprises the 2D convolutional layers and 3D convolutional layers configured to receive an output of the 2D convolutional layers as an input.
    Type: Application
    Filed: October 27, 2023
    Publication date: February 22, 2024
    Inventors: Weonsuk LEE, Hyeonsoo Lee, Gunhee Nam, Taesoo Kim
  • Method for training neural network and device thereof
    Patent number: 11823056
    Abstract: Provided is a method for training a neural network and a device thereof. The method may train a neural network with three-dimensional (3D) training image data including a plurality of two-dimensional (2D) training image data. The method may include training, at a processor, a first convolutional neural network (CNN) with the plurality of 2D training image data, wherein the first convolutional neural network comprises 2D convolutional layers. The method may further include training, at the processor, a second convolutional neural network with the 3D training image data, wherein the second convolutional neural network comprises the 2D convolutional layers and 3D convolutional layers configured to receive an output of the 2D convolutional layers as an input.
    Type: Grant
    Filed: April 7, 2020
    Date of Patent: November 21, 2023
    Assignee: LUNIT INC.
    Inventors: HyunJae Lee, Hyo-Eun Kim, Weonsuk Lee
  • METHOD FOR TRAINING NEURAL NETWORK AND DEVICE THEREOF
    Publication number: 20210125074
    Abstract: Provided is a method for training a neural network and a device thereof. The method may train a neural network with three-dimensional (3D) training image data including a plurality of two-dimensional (2D) training image data. The method may include training, at a processor, a first convolutional neural network (CNN) with the plurality of 2D training image data, wherein the first convolutional neural network comprises 2D convolutional layers. The method may further include training, at the processor, a second convolutional neural network with the 3D training image data, wherein the second convolutional neural network comprises the 2D convolutional layers and 3D convolutional layers configured to receive an output of the 2D convolutional layers as an input.
    Type: Application
    Filed: April 7, 2020
    Publication date: April 29, 2021
    Inventors: HyunJae LEE, Hyo-Eun KIM, Weonsuk LEE