Patents by Inventor Kobagapu Bhaskar RAO

Kobagapu Bhaskar RAO 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).

  • Learning device, classification device, learning method, classification method, learning program, and classification program
    Patent number: 11455502
    Abstract: A learning device acquires a plurality of images from a storage. The learning device trains a feature extraction part using a plurality of images. The learning device causes the trained feature extraction part to output a feature map of each of one or more images among the plurality of images. The learning device inputs the output feature map to a coordinate estimation part for each of one or more images, and causes the coordinate estimation part to output at least one set of coordinates of a region of a portion where the object is present in the image. The learning device extracts an image of a portion indicated by the output coordinates from the image, for each of one or more images. The learning device further trains the trained feature extraction part using the extracted image.
    Type: Grant
    Filed: May 31, 2019
    Date of Patent: September 27, 2022
    Assignee: RAKUTEN GROUP, INC.
    Inventors: Kobagapu Bhaskar Rao, Yeongnam Chae
  • Learning device, classification device, learning method, classification method, learning program, and classification program
    Patent number: 11314986
    Abstract: For each of a plurality of images, a learning device acquires first training data including an image, a class of each of one or more objects shown in the image, and the number of objects, from a storage. The learning device trains a feature extraction part, a class estimation part, and an object number estimation part using the first training data. For each of images of which the number is smaller than the plurality of images, the learning device acquires second training data including an image and coordinates of each of one or more objects in the image, from the storage. The learning device causes the trained feature extraction part to output a feature map of the image included in the second training data, and trains a coordinate estimation part using the feature map and the coordinates included in the second training data.
    Type: Grant
    Filed: May 31, 2019
    Date of Patent: April 26, 2022
    Assignee: RAKUTEN GROUP, INC.
    Inventors: Yeongnam Chae, Kobagapu Bhaskar Rao
  • LEARNING DEVICE, CLASSIFICATION DEVICE, LEARNING METHOD, CLASSIFICATION METHOD, LEARNING PROGRAM, AND CLASSIFICATION PROGRAM
    Publication number: 20210406615
    Abstract: A learning device acquires a plurality of images from a storage. The learning device trains a feature extraction part using a plurality of images. The learning device causes the trained feature extraction part to output a feature map of each of one or more images among the plurality of images. The learning device inputs the output feature map to a coordinate estimation part for each of one or more images, and causes the coordinate estimation part to output at least one set of coordinates of a region of a portion where the object is present in the image. The learning device extracts an image of a portion indicated by the output coordinates from the image, for each of one or more images. The learning device further trains the trained feature extraction part using the extracted image.
    Type: Application
    Filed: May 31, 2019
    Publication date: December 30, 2021
    Applicant: Rakuten Group, Inc.
    Inventors: Kobagapu Bhaskar RAO, Yeongnam CHAE
  • LEARNING DEVICE, CLASSIFICATION DEVICE, LEARNING METHOD, CLASSIFICATION METHOD, LEARNING PROGRAM, AND CLASSIFICATION PROGRAM
    Publication number: 20210406600
    Abstract: For each of a plurality of images, a learning device acquires first training data including an image, a class of each of one or more objects shown in the image, and the number of objects, from a storage. The learning device trains a feature extraction part, a class estimation part, and an object number estimation part using the first training data. For each of images of which the number is smaller than the plurality of images, the learning device acquires second training data including an image and coordinates of each of one or more objects in the image, from the storage. The learning device causes the trained feature extraction part to output a feature map of the image included in the second training data, and trains a coordinate estimation part using the feature map and the coordinates included in the second training data.
    Type: Application
    Filed: May 31, 2019
    Publication date: December 30, 2021
    Applicant: Rakuten, Inc.
    Inventors: Yeongnam CHAE, Kobagapu Bhaskar RAO