中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

11 records (took 0.031 seconds)

    SYSTEMS AND METHODS FOR DETERMINING WHEN TO RELABEL DATA FOR A MACHINE LEARNING MODEL
    4.
    发明申请
    SYSTEMS AND METHODS FOR DETERMINING WHEN TO RELABEL DATA FOR A MACHINE LEARNING MODEL 有权

    公开(公告)号：US20240395038A1

    公开(公告)日：2024-11-28

    申请号：US18321589

    申请日：2023-05-22

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Leonardo SARTI ,  Andrea BENERICETTI

    IPC: G06V20/40 ,  G06V10/774 ,  G06V10/778

    Abstract: A device may receive video data identifying videos, and may process the video data with a machine learning model, to determine classifications. The device may generate labels for the videos, and may calculate event severity scores and event severity labels. The device may calculate event severity incoherence scores, and may calculate user feedback scores of users associated with the device. The device may determine reviewer mistrust scores, and may calculate time review scores. The device may calculate reviewer bias scores, and may determine relabeling scores for the videos based on the event severity incoherence scores, the user feedback scores, the reviewer mistrust scores, the time review scores, and the reviewer bias scores. The device may generate new labels for one or more of the videos based on the relabeling scores, and may retrain the machine learning model, with the new labels, to generate a retrained machine learning model.

    SYSTEMS AND METHODS FOR REDUCING POWER CONSUMPTION OF EXECUTING LEARNING MODELS IN VEHICLE SYSTEMS
    6.
    发明申请
    SYSTEMS AND METHODS FOR REDUCING POWER CONSUMPTION OF EXECUTING LEARNING MODELS IN VEHICLE SYSTEMS 有权

    公开(公告)号：US20240420460A1

    公开(公告)日：2024-12-19

    申请号：US18334840

    申请日：2023-06-14

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Tomaso TRINCI ,  Tommaso BIANCONCINI ,  Leonardo TACCARI ,  Leonardo SARTI ,  Francesco SAMBO

    IPC: G06V10/82 ,  G06V20/40

    Abstract: A device may receive video data that includes a plurality of video frames, and may utilize a scheduling policy to divide the plurality of video frames into a first set of video frames and a second set of video frames. The device may process the first set of video frames, with a first convolutional neural network (CNN) model that includes one or more saliency gates, to generate first predictions and saliency maps, and may generate a trained first CNN model based on the first predictions and the saliency maps. The device may process the second set of video frames and the saliency maps, with a second CNN model that includes a saliency propagation module, to generate second predictions, and may generate a trained second CNN model based on the second predictions. The device may perform actions based on the trained first CNN model and the trained second CNN model.

    SYSTEMS AND METHODS FOR DETERMINING VIDEO SIMILARITY, RISK SCORES, AND TEXTUAL DESCRIPTIONS
    8.
    发明公开
    SYSTEMS AND METHODS FOR DETERMINING VIDEO SIMILARITY, RISK SCORES, AND TEXTUAL DESCRIPTIONS 审中-公开

    公开(公告)号：US20240096056A1

    公开(公告)日：2024-03-21

    申请号：US17933247

    申请日：2022-09-19

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Matteo SIMONCINI ,  Stefano CAPRASECCA ,  Leonardo SARTI

    IPC: G06V10/764 ,  G06V20/40 ,  G06V20/56

    CPC classification number: G06V10/764 ,  G06V20/41 ,  G06V20/56

    Abstract: A device may receive video data identifying videos associated with one or more unsafe driving events by a driver of a vehicle, and may process the video data, with a machine learning model, to determine classifications for the videos. The device may assign tags to the videos based on the classifications, and may calculate event severity scores based on the classifications. The device may calculate tag scores based on the tags assigned to the videos, and may calculate time-to-contact scores, box cross scores, day/night scores, weather scores, and road condition scores based on the video data. The device may calculate video risk scores for the videos based on the event severity scores, the tag scores, the time-to-contact scores, the box cross scores, the day/night scores, the weather scores, and the road condition scores, and may provide one or more of the video risk scores for display.

    SYSTEMS AND METHODS FOR UTILIZING MODELS TO DETECT DANGEROUS TRACKS FOR VEHICLES
    10.
    发明申请
    SYSTEMS AND METHODS FOR UTILIZING MODELS TO DETECT DANGEROUS TRACKS FOR VEHICLES 有权

    公开(公告)号：US20230080730A1

    公开(公告)日：2023-03-16

    申请号：US17447486

    申请日：2021-09-13

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Leonardo SARTI ,  Tommaso BIANCONCINI ,  Leonardo TACCARI

    IPC: G06K9/00 ,  G06K9/62 ,  G06T7/20 ,  G06K9/20 ,  G08G1/16 ,  B60W30/095 ,  B60W50/14 ,  G01P15/00

    Abstract: A device may receive accelerometer data and video data for a vehicle and may identify bounding boxes and object classes for objects near the vehicle. The device may identify tracks for the objects and may filter out tracks that are not associated with vehicles or vulnerable road users to generate one or more tracks or an indication of no tracks. The device may generate a collision cone identifying a drivable area of the vehicle to identify objects more likely to be involved in a collision and may filter out tracks from the one or more tracks, based on the bounding boxes, and to generate a subset of tracks or another indication of no tracks. The device may determine scores for the subset of tracks and may identify a track of the subset of tracks with a highest score. The device may perform actions based on the identified track.

Patent Agency Ranking