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    Systems and methods for automatically generating training image sets for an object
    1.
    发明授权
    Systems and methods for automatically generating training image sets for an object 有权

    公开(公告)号：US10885386B1

    公开(公告)日：2021-01-05

    申请号：US16571533

    申请日：2019-09-16

    Applicant: THE BOEING COMPANY

    Inventor： Nick Shadbeh Evans ,  Eric Raymond Muir ,  Tyler C. Staudinger

    IPC: G06K9/62 ,  G06T11/00 ,  G06N20/00 ,  G06T19/20

    Abstract: A computer-implemented method for generating a training image set includes retrieving, from at least one memory device, model data corresponding to a three-dimensional (3-D) model of a target object, and creating a plurality of two-dimensional (2-D) synthetic images from the model data. The 2-D synthetic images include a plurality of views of the 3-D model. The method also includes creating a plurality of semantic segmentation images by identifying a plurality of pixels that define the target object in the 2-D synthetic image, and assigning a semantic segmentation label to the identified pixels of the target object. The method further includes generating linking data associating each of the semantic segmentation labels with a corresponding one of the 2-D synthetic images, and storing the training image set including the 2-D synthetic images, the semantic segmentation labels, and the linking data.

    Integration of fuel cell with cryogenic source for cooling and reactant
    3.
    发明授权
    Integration of fuel cell with cryogenic source for cooling and reactant 审中-公开

    公开(公告)号：US10654592B2

    公开(公告)日：2020-05-19

    申请号：US15043437

    申请日：2016-02-12

    Applicant: THE BOEING COMPANY

    Inventor： Marianne E. Mata ,  Martin E. Lozano ,  Tyler C. Staudinger ,  John H. Blumer ,  Mark W. Henley

    IPC: B64G1/42 ,  H01M8/04014 ,  H01M8/04082 ,  H01M8/04701 ,  B64G1/40 ,  B64D27/24

    Abstract: A fuel cell-based power system comprises a fuel cell configured for continuously receiving a first reactant and a second reactant to produce chemical reactions that generate electrical power, water, and heat, a coolant subsystem configured for circulating a primary coolant in association with the fuel cell, thereby absorbing the generated heat, a tank configured for storing a reactant, and a reactant distribution subsystem configured for conveying the reactant from the tank to an independent system, the fuel cell as the first reactant, and the coolant subsystem as a secondary coolant to remove the absorbed heat from the primary coolant and/or a water accumulator. The secondary coolant may be conveyed to a gas thruster as a gas after the absorbed heat has been removed from the secondary coolant. The reactant may be boil off of a cryogenic liquid or vapor or gas transformed from a cryogenic liquid via a heater.

    Auto-labeling sensor data for machine learning
    4.
    发明授权
    Auto-labeling sensor data for machine learning 有权

    公开(公告)号：US11798427B2

    公开(公告)日：2023-10-24

    申请号：US17552138

    申请日：2021-12-15

    Applicant: The Boeing Company

    Inventor： Nick S. Evans ,  Eric R. Muir ,  Tyler C. Staudinger ,  Michelle D. Warren

    IPC: G08G5/00 ,  B64C39/02 ,  G06V20/17 ,  G08G5/04 ,  G06F18/214 ,  B64U101/30

    CPC classification number: G08G5/045 ,  B64C39/024 ,  G06F18/2155 ,  G06V20/17 ,  B64U2101/30

    Abstract: Solutions are provided for auto-labeling sensor data for machine learning (ML). An example includes: determining a platform's own position; recording, from a sensor aboard the platform, sensor data comprising a sensor image; receiving position data for at least one intruder object (e.g., a nearby airborne object); based at least on the position data for the intruder object and the platform's position, determining a relative position and a relative velocity of the intruder object; based at least on the relative position and a relative velocity of the intruder object and a field of view of the sensor, determining an expected position of the intruder object in the sensor image; labeling the sensor image, wherein the labeling comprises annotating the sensor image with a region of interest and an object identification; and training an artificial intelligence (AI) model using the labeled sensor image.

    Methods and systems for acoustic machine perception for an aircraft
    6.
    发明授权
    Methods and systems for acoustic machine perception for an aircraft 有权

    公开(公告)号：US11531100B2

    公开(公告)日：2022-12-20

    申请号：US16440636

    申请日：2019-06-13

    Applicant: The Boeing Company

    Inventor： Tyler C. Staudinger ,  Nick S. Evans

    IPC: G01S13/00 ,  G01S13/934 ,  G01S17/894 ,  G01M15/14 ,  G01S13/86 ,  G01S17/10 ,  G01S17/933 ,  G01S19/14 ,  G01W1/00

    Abstract: In an example, a method is described. The method includes causing one or more sensors arranged on an aircraft to acquire, over a window of time, first data associated with a first object that is within an environment of the aircraft, where the one or more sensors include one or more of a light detection and ranging (LIDAR) sensor, a radar sensor, or a camera, causing an array of microphones arranged on the aircraft to acquire, over approximately the same window of time as the first data is acquired, first acoustic data associated with the first object, and training a machine learning model by using the first acoustic data as an input value to the machine learning model and by using an azimuth, a range, an elevation, and a type of the first object identified from the first data as ground truth output labels for the machine learning model.

    Generative image synthesis for training deep learning machines
    7.
    发明授权
    Generative image synthesis for training deep learning machines 有权

    公开(公告)号：US11113864B2

    公开(公告)日：2021-09-07

    申请号：US16866320

    申请日：2020-05-04

    Applicant: The Boeing Company

    Inventor： Huafeng Yu ,  Tyler C. Staudinger

    IPC: G06T15/00

    Abstract: A set of 3D user-designed images is used to create a high volume of realistic scenes or images which can be used for training and testing deep learning machines. The system creates a high volume of scenes having a wide variety of environmental, weather-related factors as well as scenes that take into account camera noise, distortion, angle of view, and the like. A generative modeling process is used to vary objects contained in an image so that more images, each one distinct, can be used to train the deep learning model without the inefficiencies of creating videos of actual, real life scenes. Object label data can be generated for each distinct image. This and other methods can be used to artificially create new scenes that do not have to be recorded in real-life conditions and that do not require costly and time-consuming, manual labelling or tagging of objects.

    Integration of fuel cell with cryogenic source for cooling and reactant
    10.
    发明授权
    Integration of fuel cell with cryogenic source for cooling and reactant 有权

    公开(公告)号：US11459130B2

    公开(公告)日：2022-10-04

    申请号：US16703747

    申请日：2019-12-04

    Applicant: The Boeing Company

    Inventor： Marianne E. Mata ,  Martin E. Lozano ,  Tyler C. Staudinger ,  John H. Blumer ,  Mark W. Henley

    IPC: B64G1/42 ,  H01M8/04014 ,  H01M8/04082 ,  H01M8/04701 ,  B64G1/40 ,  B64D27/24

    Abstract: A fuel cell-based power system comprises a fuel cell configured for continuously receiving a first reactant and a second reactant to produce chemical reactions that generate electrical power, water, and heat, a coolant subsystem configured for circulating a primary coolant in association with the fuel cell, thereby absorbing the generated heat, a tank configured for storing a reactant, and a reactant distribution subsystem configured for conveying the reactant from the tank to an independent system, the fuel cell as the first reactant, and the coolant subsystem as a secondary coolant to remove the absorbed heat from the primary coolant and/or a water accumulator. The secondary coolant may be conveyed to a gas thruster as a gas after the absorbed heat has been removed from the secondary coolant. The reactant may boil off of a cryogenic liquid or vapor or gas transformed from a cryogenic liquid via a heater.

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