RIS WITH LC
    363.
    发明公开
    RIS WITH LC 审中-公开

    公开(公告)号:US20240072451A1

    公开(公告)日:2024-02-29

    申请号:US18135352

    申请日:2023-04-17

    CPC classification number: H01Q15/0013 H01Q3/44

    Abstract: There is provided an RIS with LC. According to an embodiment, an RIS includes: a plurality of RIS elements; and an RIS controller configured to control the RIS elements to steer an RF signal entering, and the RIS element includes: a first substrate; a second substrate; an antenna disposed between the first substrate and the second substrate; a ground disposed between the first substrate and the second substrate; and an LC phase shifter disposed between the antenna and the ground to change a phase of the RF signal entering. Accordingly, a phase shifter for changing a phase of an RF signal entering is implemented by using LC, so that an RIS may be implemented on a transparent window without obstructing light or a field of vision, and also, an outdoor reflect mode and an indoor transmit mode may be supported by one RIS.

    SELF-DIRECTED VISUAL INTELLIGENCE SYSTEM
    365.
    发明公开

    公开(公告)号:US20240062522A1

    公开(公告)日:2024-02-22

    申请号:US17968986

    申请日:2022-10-19

    CPC classification number: G06V10/774 G06V20/46

    Abstract: There is provided a self-directed visual intelligence system, The self-directed visual intelligence system according to an embodiment prepares data necessary for training a visual intelligence model when a change in a visual context of a real world is recognized, configures a visual intelligence model and configures training data of the visual intelligence model, based on the changed visual context of the real world, trains the configured visual intelligence model with the training data, and evaluates performance of the trained visual intelligence model. Accordingly, the visual intelligence model is corrected/improved in a self-directed way according to a change in a visual context of a real world, and is grown/advanced by itself, so that performance of the visual intelligence model is maintained in a best state even in response to any change in the context of the real world.

    METHOD AND SYSTEM FOR GENERATING AI TRAINING HIERARCHICAL DATASET INCLUDING DATA ACQUISITION CONTEXT INFORMATION

    公开(公告)号:US20240005197A1

    公开(公告)日:2024-01-04

    申请号:US17623132

    申请日:2020-12-29

    CPC classification number: G06N20/00

    Abstract: Provided are a method and a system for generating an AI training hierarchical dataset including data acquisition context information. A GT dataset generation method according to an embodiment of the present disclosure includes: acquiring and storing vehicle data; acquiring and storing sensor data generated at a sensor installed in a vehicle; and generating and storing context information which is information regarding a context at a time when the data is acquired. Accordingly, in generating a GT descriptor, various contexts, conditions at the time when data is acquired may be made to be easily analyzed, classified on the GT descriptor through a hierarchical dataset, which hierarchically describes context information at the time when sensor data is acquired on the descriptor, so that an AI network is effectively trained, and eventually, has high recognition performance.

    Method for generating hollow structure based on 2D laminated cross-sectional outline for 3D printing

    公开(公告)号:US11798231B2

    公开(公告)日:2023-10-24

    申请号:US17623104

    申请日:2020-11-10

    CPC classification number: G06T7/20

    Abstract: Provided is a method for generating a hollow structure of a 3D model on the basis of a 2D laminated cross-sectional outline to reduce the amount of using a material or the weight of a printed matter during laminating and manufacturing. The method for generating a hollow structure based on a 2D laminated cross-sectional outline, according to an embodiment of the present invention, comprises the steps of: slicing the 3D model; generating a hollow structure outline on the basis of the result of the slicing; detecting an overhang area between adjacent hollow structure outlines; recalculating the hollow structure outline according to the result of detecting the overhang area; and generating a hollow structure mesh on the basis of the recalculated hollow structure outline. Accordingly, because 2D laminated cross-sectional data is used, a hollow structure can be generated without separate data processing, thereby reducing a calculation burden. In addition, because the hollow structure is processed so that an overhang area is not generated when generating the hollow structure, a support is not needed therein, thereby making post-processing easy.

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