知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

35 records (took 0.02 seconds)

    Brake Light Detection
    1.
    发明申请
    Brake Light Detection 有权

    公开(公告)号：US20240371150A1

    公开(公告)日：2024-11-07

    申请号：US18774595

    申请日：2024-07-16

    Applicant: Ford Global Technologies, LLC.

    Inventor： Maryam Moosaei ,  Guy Hotson ,  Parsa Mahmoudieh ,  Vidya Nariyambut Murali

    IPC: G06V10/82 ,  G06V10/764 ,  G06V20/58

    Abstract: Systems, methods, and devices for detecting brake lights are disclosed herein. A system includes a mode component, a vehicle region component, and a classification component. The mode component is configured to select a night mode or day mode based on a pixel brightness in an image frame. The vehicle region component is configured to detect a region corresponding to a vehicle based on data from a range sensor when in a night mode or based on camera image data when in the day mode. The classification component is configured to classify a brake light of the vehicle as on or off based on image data in the region corresponding to the vehicle.

    Object detection using recurrent neural network and concatenated feature map
    4.
    发明授权
    Object detection using recurrent neural network and concatenated feature map 有权

    公开(公告)号：US11062167B2

    公开(公告)日：2021-07-13

    申请号：US16576277

    申请日：2019-09-19

    Applicant: Ford Global Technologies, LLC.

    Inventor： Guy Hotson ,  Parsa Mahmoudieh ,  Vidya Nariyambut Murali

    IPC: G06K9/46 ,  G06T7/70 ,  G06K9/62 ,  G06K9/00

    Abstract: According to one embodiment, a system includes a sensor component and a detection component. The sensor component is configured to obtain a first stream of sensor data and a second stream of sensor data, wherein each of the first stream and second stream comprise a plurality of sensor frames. The detection component is configured to generate a concatenated feature map based on a sensor frame of a first type and a sensor frame of a second type. The detection component is configured to detect one or more objects based on the concatenated feature map. One or more of generating and detecting comprises generating or detecting using a neural network with a recurrent connection that feeds information about features or objects from previous frames.

    Brake light detection
    5.
    发明授权
    Brake light detection 有权

    公开(公告)号：US10853673B2

    公开(公告)日：2020-12-01

    申请号：US16261300

    申请日：2019-01-29

    Applicant: Ford Global Technologies, LLC.

    Inventor： Maryam Moosaei ,  Guy Hotson ,  Parsa Mahmoudieh ,  Vidya Nariyambut Murali

    IPC: G06K9/00

    Abstract: Systems, methods, and devices for detecting brake lights are disclosed herein. A system includes a mode component, a vehicle region component, and a classification component. The mode component is configured to select a night mode or day mode based on a pixel brightness in an image frame. The vehicle region component is configured to detect a region corresponding to a vehicle based on data from a range sensor when in a night mode or based on camera image data when in the day mode. The classification component is configured to classify a brake light of the vehicle as on or off based on image data in the region corresponding to the vehicle.

    Shared Processing with Deep Neural Networks
    9.
    发明申请
    Shared Processing with Deep Neural Networks 审中-公开

    公开(公告)号：US20190065944A1

    公开(公告)日：2019-02-28

    申请号：US15687247

    申请日：2017-08-25

    Applicant: Ford Global Technologies, LLC

    Inventor： Guy Hotson ,  Vidya Nariyambut Murali ,  Gintaras Vincent Puskorius

    IPC: G06N3/08 ,  G06N3/04

    Abstract: A system includes a processor for performing one or more autonomous driving or assisted driving tasks based on a neural network. The neural network includes a base portion for performing feature extraction simultaneously for a plurality of tasks on a single set of input data. The neural network includes a plurality of subtask portions for performing the plurality of tasks based on feature extraction output from the base portion. Each of the plurality of subtask portions comprise nodes or layers of a neutral network trained on different sets of training data, and the base portion comprises nodes or layers of a neural network trained using each of the different sets of training data constrained by elastic weight consolidation to limit the base portion from forgetting a previously learned task.

    Object detection using recurrent neural network and concatenated feature map
    10.
    发明授权
    Object detection using recurrent neural network and concatenated feature map 有权

    公开(公告)号：US10198655B2

    公开(公告)日：2019-02-05

    申请号：US15414383

    申请日：2017-01-24

    Applicant: Ford Global Technologies, LLC

    Inventor： Guy Hotson ,  Parsa Mahmoudieh ,  Vidya Nariyambut Murali

    IPC: G06K9/00 ,  G06K9/46 ,  G06T7/70 ,  G06K9/62

    Abstract: According to one embodiment, a system includes a sensor component and a detection component. The sensor component is configured to obtain a first stream of sensor data and a second stream of sensor data, wherein each of the first stream and second stream comprise a plurality of sensor frames. The detection component is configured to generate a concatenated feature map based on a sensor frame of a first type and a sensor frame of a second type. The detection component is configured to detect one or more objects based on the concatenated feature map. One or more of generating and detecting comprises generating or detecting using a neural network with a recurrent connection that feeds information about features or objects from previous frames.

Patent Agency Ranking