Patents by Inventor Varsha Vivek

Varsha Vivek 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).

  • Importance sampling for segmentation network training modification
    Patent number: 11189031
    Abstract: Methods and systems regarding importance sampling for the modification of a training procedure used to train a segmentation network are disclosed herein. A disclosed method includes segmenting an image using a trainable directed graph to generate a segmentation, displaying the segmentation, receiving a first selection directed to the segmentation, and modifying a training procedure for the trainable directed graph using the first selection. In a more specific method, the training procedure alters a set of trainable values associated with the trainable directed graph based on a delta between the segmentation and a ground truth segmentation, the first selection is spatially indicative with respect to the segmentation, and the delta is calculated based on the first selection.
    Type: Grant
    Filed: May 14, 2019
    Date of Patent: November 30, 2021
    Assignee: Matterport, Inc.
    Inventors: Gary Bradski, Ethan Rublee, Mona Fathollahi, Michael Tetelman, Ian Meeder, Varsha Vivek, William Nguyen
  • IMPORTANCE SAMPLING FOR SEGMENTATION NETWORK TRAINING MODIFICATION
    Publication number: 20200364873
    Abstract: Methods and systems regarding importance sampling for the modification of a training procedure used to train a segmentation network are disclosed herein. A disclosed method includes segmenting an image using a trainable directed graph to generate a segmentation, displaying the segmentation, receiving a first selection directed to the segmentation, and modifying a training procedure for the trainable directed graph using the first selection. In a more specific method, the training procedure alters a set of trainable values associated with the trainable directed graph based on a delta between the segmentation and a ground truth segmentation, the first selection is spatially indicative with respect to the segmentation, and the delta is calculated based on the first selection.
    Type: Application
    Filed: May 14, 2019
    Publication date: November 19, 2020
    Applicant: Matterport, Inc.
    Inventors: Gary Bradski, Ethan Rublee, Mona Fathollahi, Michael Tetelman, Ian Meeder, Varsha Vivek, William Nguyen