Patents by Inventor Sriya Sarathy

Sriya Sarathy 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).

  • Patent number: 12072442
    Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
    Type: Grant
    Filed: November 22, 2021
    Date of Patent: August 27, 2024
    Assignee: NVIDIA Corporation
    Inventors: Tommi Koivisto, Pekka Janis, Tero Kuosmanen, Timo Roman, Sriya Sarathy, William Zhang, Nizar Assaf, Colin Tracey
  • Publication number: 20240192320
    Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
    Type: Application
    Filed: February 20, 2024
    Publication date: June 13, 2024
    Inventors: Tommi Koivisto, Pekka Janis, Tero Kuosmanen, Timo Roman, Sriya Sarathy, William Zhang, Nizar Assaf, Colin Tracey
  • Publication number: 20220101635
    Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
    Type: Application
    Filed: November 22, 2021
    Publication date: March 31, 2022
    Inventors: Tommi Koivisto, Pekka Janis, Tero Kuosmanen, Timo Roman, Sriya Sarathy, William Zhang, Nizar Assaf, Colin Tracey
  • Patent number: 11210537
    Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
    Type: Grant
    Filed: February 15, 2019
    Date of Patent: December 28, 2021
    Assignee: NVIDIA Corporation
    Inventors: Tommi Koivisto, Pekka Janis, Tero Kuosmanen, Timo Roman, Sriya Sarathy, William Zhang, Nizar Assaf, Colin Tracey
  • Publication number: 20190258878
    Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
    Type: Application
    Filed: February 15, 2019
    Publication date: August 22, 2019
    Inventors: Tommi Koivisto, Pekka Janis, Tero Kuosmanen, Timo Roman, Sriya Sarathy, William Zhang, Nizar Assaf, Colin Tracey