FLYING MACHINE AND FLYING MACHINE USAGE METHOD

    公开(公告)号:US20170274995A1

    公开(公告)日:2017-09-28

    申请号:US15442796

    申请日:2017-02-27

    Abstract: A flying machine includes: a flying machine body that includes a rotor blade; a protective member that forms a frame shape inside which the rotor blade is disposed, that is rotatably fixed to both end portions of the flying machine body, and that is pipe shaped; and a connecting wire that passes through an inner portion of the protective member to connect the flying machine body and an external device together.

    INPUT DEVICE AND INPUT METHOD
    13.
    发明申请
    INPUT DEVICE AND INPUT METHOD 有权
    输入设备和输入方法

    公开(公告)号:US20150193003A1

    公开(公告)日:2015-07-09

    申请号:US14561965

    申请日:2014-12-05

    Inventor: Moyuru YAMADA

    Abstract: A device that is worn on a portion of a user's body and inputs a command into a controller, includes a sensor that obtains angular velocities and an acceleration in a first coordinate system fixed in the input device, a processor that performs setting a second coordinate system for a reference posture of the user, calculating a rotation matrix that converts the angular velocities in the first coordinate system into angular velocities in the second coordinate system using the acceleration in the first coordinate system, calculating feature amounts in the second coordinate system using the angular velocities in the second coordinate system, and specifying the command using the feature amounts, and a transmitter that transmits the command to the controller.

    Abstract translation: 佩戴在用户身体的一部分并将命令输入到控制器中的装置包括:传感器,其获取固定在输入装置中的第一坐标系中的角速度和加速度;处理器,其执行设定第二坐标系 对于用户的参考姿势,计算使用第一坐标系中的加速度将第一坐标系中的角速度转换成第二坐标系中的角速度的旋转矩阵,使用角度计算第二坐标系中的特征量 第二坐标系中的速度,以及使用特征量指定命令,以及将命令发送到控制器的发射器。

    SCENE DETECTION
    14.
    发明申请

    公开(公告)号:US20250046079A1

    公开(公告)日:2025-02-06

    申请号:US18787047

    申请日:2024-07-29

    Inventor: Moyuru YAMADA

    Abstract: A computer-implemented method comprising: based on an input scene graph, generating a plurality of graph vectors; encoding an input image to generate a plurality of image vectors; performing an update process to generate a plurality of updated graph vectors and at least one updated object query vector, comprising: updating the at least one object query vector based on the plurality of graph vectors; updating the at least one object query vector based on the plurality of image vectors; and updating the plurality of graph vectors based on the at least one object query vector; extracting from the at least one updated object query vector a region and a category of the at least one object; and computing a matching score indicating a similarity between the input image and the input scene graph based on the at least one updated object query vector and the plurality of updated graph vectors.

    STORAGE MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE

    公开(公告)号:US20230409630A1

    公开(公告)日:2023-12-21

    申请号:US18176809

    申请日:2023-03-01

    Inventor: Moyuru YAMADA

    CPC classification number: G06F16/5846

    Abstract: A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process includes receiving, from a server, a plurality of pieces of first feature data that correspond to each of a plurality of pieces of image data; acquiring text data included in search conditions, the search conditions being transmitted from a client device; receiving second feature data that corresponds to the text data and is transmitted from the server, in response to transmitting the text data to the server; and acquiring a plurality of degrees of similarity between the plurality of pieces of the first feature data and the second feature data.

    STORAGE MEDIUM, MACHINE LEARNING APPARATUS, AND MACHINE LEARNING METHOD

    公开(公告)号:US20230114374A1

    公开(公告)日:2023-04-13

    申请号:US17959524

    申请日:2022-10-04

    Inventor: Moyuru YAMADA

    Abstract: A storage medium storing a machine learning program that causes a computer to execute a process that includes generating a feature of a training image by inputting the training image to a first model; generating text corresponding to the training image by inputting first training text to the first model; generating a feature of second training text, for which a correct answer as to whether the second training text corresponds to the training image is known, by inputting the second training text to a second model; and changing a parameter of the first model and a parameter of the second model so that a first error between the first training text and the generated text corresponding to the training image and a second error between the correct answer and a degree of similarity between the feature of the training image and the feature of the second training text decrease.

    STORAGE MEDIUM, MACHINE LEARNING METHOD, AND OUTPUT DEVICE

    公开(公告)号:US20220164588A1

    公开(公告)日:2022-05-26

    申请号:US17472717

    申请日:2021-09-13

    Inventor: Moyuru YAMADA

    Abstract: A non-transitory computer-readable storage medium storing a machine learning program for causing a computer to execute a process includes acquiring a plurality of vectors that indicate a feature of each of a plurality of partial images extracted from an image; calculating a same number of vectors as a certain number of vectors based on the plurality of vectors and the certain number of vectors; and changing parameters of a neural network by executing machine learning based on vectors that indicate a feature of text and the same number of vectors.

    DEVICE AND METHOD FOR ESTIMATING DEGREE OF FREEDOM FOR MOVEMENT

    公开(公告)号:US20190227167A1

    公开(公告)日:2019-07-25

    申请号:US16240914

    申请日:2019-01-07

    Inventor: Moyuru YAMADA

    Abstract: A device for estimating a degree of freedom for movement includes a memory, and a processor coupled to the memory and the processor configured to acquire first three-dimensional information of a target object at a first time and second three-dimensional information of the target object at a second time, specify a movable portion of the target object according to a difference between the first three-dimensional information and the second three-dimensional information, estimate the degree of freedom for movement of the movable portion included in the target object according to displacement of the movable portion between the first three-dimensional information and the second three-dimensional information, and assign degree of freedom information for indicating the degree of freedom for movement to a three-dimensional model for representing the target object, based on the estimated degree of freedom for movement of the movable portion.

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