Patents by Inventor Yumi OZAKI

Yumi OZAKI 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).

  • Abnormality detection device, abnormality detection method, and storage medium
    Patent number: 11501163
    Abstract: An abnormality detection device according to an embodiment includes a detector, a remover, and a learner. The detector detects first abnormal data in detection target data which is an abnormality detection target by inputting the detection target data to a first autoencoder which performed learning based on first learning target data which is a learning target. The remover removes data associated with the first abnormal data from the first learning target data to generate second learning target data by inputting the first learning target data to a second autoencoder which performed learning based on the first abnormal data detected by the detector. The learner causes the first autoencoder to perform learning based on the second learning target data generated by the remover.
    Type: Grant
    Filed: September 25, 2017
    Date of Patent: November 15, 2022
    Assignees: Kabushiki Kaisha Toshiba, Toshiba Digital Solutions Corporation
    Inventors: Jun Ohashi, Yumi Ozaki
  • ABNORMALITY DETECTION DEVICE, ABNORMALITY DETECTION METHOD, AND STORAGE MEDIUM
    Publication number: 20200057939
    Abstract: An abnormality detection device according to an embodiment includes a detector, a remover, and a learner. The detector detects first abnormal data in detection target data which is an abnormality detection target by inputting the detection target data to a first autoencoder which performed learning based on first learning target data which is a learning target. The remover removes data associated with the first abnormal data from the first learning target data to generate second learning target data by inputting the first learning target data to a second autoencoder which performed learning based on the first abnormal data detected by the detector. The learner causes the first autoencoder to perform learning based on the second learning target data generated by the remover.
    Type: Application
    Filed: September 25, 2017
    Publication date: February 20, 2020
    Applicants: Kabushiki Kaisha Toshiba, Toshiba Digital Solutions Corporation
    Inventors: Jun OHASHI, Yumi OZAKI