Patents by Inventor Soonhyun Noh

Soonhyun Noh 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).

  • Camera-based positioning system using learning
    Patent number: 10996060
    Abstract: A device, system, and methods are described to perform machine-learning camera-based indoor mobile positioning. The indoor mobile positioning may utilize inexact computing, wherein a small decrease in accuracy is used to obtain significant computational efficiency. Hence, the positioning may be performed using a smaller memory overhead at a faster rate and with lower energy cost than previous implementations. The positioning may not involve any communication (or data transfer) with any other device or the cloud, providing privacy and security to the device. A hashing-based image matching algorithm may be used which is cheaper, both in energy and computation cost, over existing state-of-the-art matching techniques. This significant reduction allows end-to-end computation to be performed locally on the mobile device.
    Type: Grant
    Filed: August 28, 2017
    Date of Patent: May 4, 2021
    Assignees: William Marsh Rice University, Seoul National University R&DB Foundation
    Inventors: Anshumali Shrivastava, Chen Luo, Krishna Palem, Yongshik Moon, Soonhyun Noh, Daedong Park, Seongsoo Hong
  • CAMERA-BASED POSITIONING SYSTEM USING LEARNING
    Publication number: 20200256679
    Abstract: A device, system, and methods are described to perform machine-learning camera-based indoor mobile positioning. The indoor mobile positioning may utilize inexact computing, wherein a small decrease in accuracy is used to obtain significant computational efficiency. Hence, the positioning may be performed using a smaller memory overhead at a faster rate and with lower energy cost than previous implementations. The positioning may not involve any communication (or data transfer) with any other device or the cloud, providing privacy and security to the device. A hashing-based image matching algorithm may be used which is cheaper, both in energy and computation cost, over existing state-of-the-art matching techniques. This significant reduction allows end-to-end computation to be performed locally on the mobile device.
    Type: Application
    Filed: August 28, 2017
    Publication date: August 13, 2020
    Inventors: Anshumali Shrivastava, Chen Luo, Krishna Palem, Yongshik Moon, Soonhyun Noh, Daedong Park, Seongsoo Hong
  • CUSTOMER SERVICE SYSTEMS AND PORTALS
    Publication number: 20190195634
    Abstract: A device, system, and methods are described to perform machine-learning camera-based indoor mobile positioning. The indoor mobile positioning may utilize inexact computing, wherein a small decrease in accuracy is used to obtain significant computational efficiency. Hence, the positioning may be performed using a smaller memory overhead at a faster rate and with lower energy cost than previous implementations. The positioning may not involve any communication (or data transfer) with any other device or the cloud, providing privacy and security to the device. A hashing-based image matching algorithm may be used which is cheaper, both in energy and computation cost, over existing state-of-the-art matching techniques. This significant reduction allows end-to-end computation to be performed locally on the mobile device.
    Type: Application
    Filed: August 28, 2017
    Publication date: June 27, 2019
    Inventors: Anshumali Shrivastava, Chen Luo, Krishna Palem, Yongshik Moon, Soonhyun Noh, Daedong Park, Seongsoo Hong