Patents by Inventor Tsubasa HIRAKAWA

Tsubasa HIRAKAWA 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: 20240362915
    Abstract: A computer vision system, with at least one processor configured to: acquire, from a sports match video, moving image data of a first period and moving image data of a second period; by using a first machine learning model, generate, based on the moving image data of the first period, first estimation data and second estimation data for an estimation period; by using a second machine learning model, generate, based on the moving image data of the second period, the first estimation data and the second estimation data for the estimation period; and generate determination data based on the first estimation data and the second estimation data that are output from the first machine learning model and the first estimation data and the second estimation data that are output from the second machine learning model.
    Type: Application
    Filed: June 27, 2022
    Publication date: October 31, 2024
    Inventors: Takayoshi YAMASHITA, Hironobu FUJIYOSHI, Tsubasa HIRAKAWA, Mitsuru NAKAZAWA, Yeongnam CHAE, Bjorn STENGER
  • Publication number: 20240338930
    Abstract: A computer vision system, with at least one processor configured to: acquire, from a sports match video, a plurality of pieces of consecutive image data indicating a portion of the sports match video, the plurality of pieces of consecutive image data including a plurality of pieces of first consecutive image data that are consecutive; and execute an estimation, by using a machine learning model, of whether the portion is of a predetermined scene type, wherein, in the estimation, the at least one processor is configured to.
    Type: Application
    Filed: March 28, 2022
    Publication date: October 10, 2024
    Inventors: Takayoshi YAMASHITA, Hironobu FUJIYOSHI, Tsubasa HIRAKAWA, Mitsuru NAKAZAWA, Yeongnam CHAE, Bjorn STENGER
  • Publication number: 20240320956
    Abstract: A computer vision system, with at least one processor configured to: acquire, from a sports match video, a plurality of pieces of consecutive image data indicating a portion of the sports match video, the plurality of pieces of consecutive image data including a plurality of pieces of first consecutive image data that are consecutive and a plurality of pieces of second consecutive image data that are consecutive after the plurality of pieces of first consecutive image data; and execute an estimation, by using a machine learning model, of whether the portion is of a predetermined scene type.
    Type: Application
    Filed: March 28, 2022
    Publication date: September 26, 2024
    Inventors: Takayoshi YAMASHITA, Hironobu FUJIYOSHI, Tsubasa HIRAKAWA, Mitsuru NAKAZAWA, Yeongnam CHAE, Bjorn STENGER
  • Publication number: 20240104914
    Abstract: A learning model generates a plurality of prototype vectors and generates an integrated similarity vector that indicates similarity between an input image and each prototype for a plurality of prototypes in accordance with similarity between one prototype vector and each pixel vector in a feature map acquired from an CNN. An image processing apparatus obtains prototype belongingness (distributed prototype belongingness) for each image by distributing prototype belongingness of a belonged prototype of each class to each of two or more images that belong to one class. Then, the learning model is subjected to machine learning in accordance with the distributed prototype belongingness of each prototype vector for each image so that each prototype vector is brought closer to any pixel vector in the feature map corresponding to each image.
    Type: Application
    Filed: September 20, 2023
    Publication date: March 28, 2024
    Applicants: Glory Ltd., Chubu University Educational Foundation
    Inventors: Yuki UKAI, Hironobu FUJIYOSHI, Takayoshi YAMASHITA, Tsubasa HIRAKAWA
  • Publication number: 20240087098
    Abstract: A training method includes: generating a first image by adding noise to a first area; generating a second image by adding noise to a second area; generating a combined image by weighted addition of the first image and the second image; generating a first training label for the first image; generating a second training label for the second image; generating a combined training label by weighted addition of the first training label and the second training label; and generating a learning model by machine learning using the combined image and the combined training label.
    Type: Application
    Filed: November 17, 2023
    Publication date: March 14, 2024
    Inventors: Hironobu FUJIYOSHI, Takayoshi YAMASHITA, Tsubasa HIRAKAWA, Kazuki KOZUKA
  • Patent number: 11776320
    Abstract: An information processing method includes processing of: acquiring, from a plurality of time-series images in which an object is captured, first information including at least a plurality of positions or a plurality of sizes of the object; executing prediction processing of predicting second information including at least one of a position or a size of the object at a next time point in a time-series based on the first information and recursively executing the prediction processing based on the first information and the second information to predict the second information of the object at a time point further next to the next time point; executing recognition processing of recognizing motion of the object based on the second information; and determining a total number of times of recursion of the prediction processing based on a result of the recognition processing.
    Type: Grant
    Filed: June 2, 2021
    Date of Patent: October 3, 2023
    Assignee: PANASONIC INTELLECTUAL PROPERTY CORPORATION OF AMERICA
    Inventors: Yasunori Ishii, Hironobu Fujiyoshi, Takayoshi Yamashita, Tsubasa Hirakawa
  • Publication number: 20210286982
    Abstract: An information processing method includes processing of: acquiring, from a plurality of time-series images in which an object is captured, first information including at least a plurality of positions or a plurality of sizes of the object; executing prediction processing of predicting second information including at least one of a position or a size of the object at a next time point in a time-series based on the first information and recursively executing the prediction processing based on the first information and the second information to predict the second information of the object at a time point further next to the next time point; executing recognition processing of recognizing motion of the object based on the second information; and determining a total number of times of recursion of the prediction processing based on a result of the recognition processing.
    Type: Application
    Filed: June 2, 2021
    Publication date: September 16, 2021
    Inventors: Yasunori ISHII, Hironobu FUJIYOSHI, Takayoshi YAMASHITA, Tsubasa HIRAKAWA
  • Patent number: 10062161
    Abstract: An endoscopic image diagnosis support system (100) includes: a memory (10) that stores learning images pre-classified into pathological types; and a processor (20) that, given an endoscopic image, performs feature value matching between an image of an identification target region in the endoscopic image and the learning images, to identify the pathological types in the identification target region.
    Type: Grant
    Filed: February 2, 2015
    Date of Patent: August 28, 2018
    Assignee: HIROSHIMA UNIVERSITY
    Inventors: Tetsushi Koide, HoangAnh Tuan, Shigeto Yoshida, Tsubasa Mishima, Satoshi Shigemi, Toru Tamaki, Tsubasa Hirakawa, Rie Miyaki, Kouki Sugi
  • Publication number: 20160350912
    Abstract: An endoscopic image diagnosis support system (100) includes: a memory (10) that stores learning images pre-classified into pathological types; and a processor (20) that, given an endoscopic image, performs feature value matching between an image of an identification target region in the endoscopic image and the learning images, to identify the pathological types in the identification target region.
    Type: Application
    Filed: February 2, 2015
    Publication date: December 1, 2016
    Applicant: HIROSHIMA UNIVERSITY
    Inventors: Tetsushi KOIDE, HoangAnh TUAN, Shigeto YOSHIDA, Tsubasa MISHIMA, Satoshi SHIGEMI, Toru TAMAKI, Tsubasa HIRAKAWA, Rie MIYAKI, Kouki SUGI