Patents by Inventor Jithendar ANUMULA

Jithendar ANUMULA 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: 12106214
    Abstract: A sensor transformation attention network (STAN) model including sensors configured to collect input signals, attention modules configured to calculate attention scores of feature vectors corresponding to the input signals, a merge module configured to calculate attention values of the attention scores, and generate a merged transformation vector based on the attention values and the feature vectors, and a task-specific module configured to classify the merged transformation vector is provided.
    Type: Grant
    Filed: October 18, 2022
    Date of Patent: October 1, 2024
    Assignees: SAMSUNG ELECTRONICS CO., LTD., UNIVERSITAET ZUERICH
    Inventors: Stefan Braun, Daniel Neil, Enea Ceolini, Jithendar Anumula, Shih-Chii Liu
  • Publication number: 20230045790
    Abstract: A sensor transformation attention network (STAN) model including sensors configured to collect input signals, attention modules configured to calculate attention scores of feature vectors corresponding to the input signals, a merge module configured to calculate attention values of the attention scores, and generate a merged transformation vector based on the attention values and the feature vectors, and a task-specific module configured to classify the merged transformation vector is provided.
    Type: Application
    Filed: October 18, 2022
    Publication date: February 16, 2023
    Applicants: SAMSUNG ELECTRONICS CO., LTD., Universitaet Zuerich
    Inventors: Stefan BRAUN, Daniel Neil, Enea Ceolini, Jithendar Anumula, Shih-Chii Lui
  • Publication number: 20230028426
    Abstract: A method and a system described herein provide optimizing image and/or video compression for machine perception. According to an aspect, the method comprises receiving a raw image frame from a camera sensor; detecting a predefined object in the raw image frame and marking a region around the predefined object within the raw image frame as ROI. Based on the ROI, a partitioning scheme, a prediction mode, and quantization parameter are determined for improving coding efficiency. Machine perception efficiency is improved by selecting a quantization parameter table used for compressing and encoding the raw image or video frame based on a selected machine vision task. The selection of the quantization parameter table is based on training of the selected machine vision task using cost function optimization.
    Type: Application
    Filed: July 15, 2021
    Publication date: January 26, 2023
    Inventors: Muhammad Nadeem, Gergely Zombori, Jithendar Anumula, Markus Kopf
  • Patent number: 11533484
    Abstract: A method and a system described herein provide optimizing image and/or video compression for machine perception. According to an aspect, the method comprises receiving a raw image frame from a camera sensor; detecting a predefined object in the raw image frame and marking a region around the predefined object within the raw image frame as ROI. Based on the ROI, a partitioning scheme, a prediction mode, and quantization parameter are determined for improving coding efficiency. Machine perception efficiency is improved by selecting a quantization parameter table used for compressing and encoding the raw image or video frame based on a selected machine vision task. The selection of the quantization parameter table is based on training of the selected machine vision task using cost function optimization.
    Type: Grant
    Filed: July 15, 2021
    Date of Patent: December 20, 2022
    Assignee: TERAKI GMBH
    Inventors: Jithendar Anumula, Bernhard Kaplan, Daniel Lampert Richart
  • Patent number: 11501154
    Abstract: A sensor transformation attention network (STAN) model including sensors, attention modules, a merge module and a task-specific module is provided. The attention modules calculate attention scores of feature vectors corresponding to the input signals collected by the sensors. The merge module calculates attention values of the attention scores, and generates a merged transformation vector based on the attention values and the feature vectors. The task-specific module classifies the merged transformation vector.
    Type: Grant
    Filed: March 5, 2018
    Date of Patent: November 15, 2022
    Assignees: SAMSUNG ELECTRONICS CO., LTD., UNIVERSITAET ZUERICH
    Inventors: Stefan Braun, Daniel Neil, Enea Ceolini, Jithendar Anumula, Shih-Chii Liu
  • Publication number: 20180336466
    Abstract: A sensor transformation attention network (STAN) model including sensors configured to collect input signals, attention modules configured to calculate attention scores of feature vectors corresponding to the input signals, a merge module configured to calculate attention values of the attention scores, and generate a merged transformation vector based on the attention values and the feature vectors, and a task-specific module configured to classify the merged transformation vector is provided.
    Type: Application
    Filed: March 5, 2018
    Publication date: November 22, 2018
    Applicants: SAMSUNG ELECTRONICS CO., LTD., UNIVERSITAET ZUERICH
    Inventors: Stefan BRAUN, Daniel NEIL, Enea CEOLINI, Jithendar ANUMULA, Shih-Chii LIU