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    RESOURCE PUSHING METHOD AND APPARATUS, DEVICE, AND STORAGE MEDIUM
    1.
    发明申请
    RESOURCE PUSHING METHOD AND APPARATUS, DEVICE, AND STORAGE MEDIUM 有权

    公开(公告)号：US20220284327A1

    公开(公告)日：2022-09-08

    申请号：US17725429

    申请日：2022-04-20

    Applicant: Tencent Technology (Shenzhen) Company Limited

    Inventor： Shaoliang ZHANG ,  Rui Wang ,  Ruobing Xie ,  Zhihong Yang ,  Feng Xia ,  Leyu Lin

    IPC: G06N5/04 ,  G06F16/9535 ,  G06N5/02

    Abstract: This application discloses a resource pushing method performed by a computer device. The method includes: obtaining a target recommendation model and a preference feature and a candidate resource set corresponding to a target object, the preference feature including at least a channel preference feature and a content preference feature; obtaining at least one target resource from the candidate resource set based on the target recommendation model and the preference feature; and pushing the at least one target resource to the target object. Such a resource pushing process integrates preferences of the target object in different dimensions, so that the target resource pushed to the target object not only conforms to channel preferences of the target object, but also conforms to content references of the target object, which is beneficial to improving the resource pushing effect, and further increasing the click-through rates (CTRs) of the pushed resources.

    Border detection method, server and storage medium
    2.
    发明授权
    Border detection method, server and storage medium 有权

    公开(公告)号：US11328427B2

    公开(公告)日：2022-05-10

    申请号：US16578672

    申请日：2019-09-23

    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

    Inventor： Xing Sun ,  Rui Wang ,  Xiaowei Guo

    IPC: G06T7/13 ,  G06K9/62

    Abstract: Provided is a border detection method, server, and storage medium. The method including detecting a plurality of first straight line segments in a to-be-detected image, the to-be-detected image comprising a target region of a to-be-determined border; generating a plurality of first candidate borders of the target region according to the plurality of first straight line segments; obtaining a plurality of second candidate borders of the target region from the plurality of first candidate borders; extracting border features of the plurality of second candidate borders; and obtaining an actual border of the target region from the plurality of second candidate borders according to the border features of the plurality of second candidate borders and a border detection model, the border detection model being used to determine a detected value of each candidate border, and the detected value representing a similarity between each candidate border and the actual border.

    Graph centrality calculation method and apparatus, and storage medium
    3.
    发明授权
    Graph centrality calculation method and apparatus, and storage medium 有权

    公开(公告)号：US10936765B2

    公开(公告)日：2021-03-02

    申请号：US16227736

    申请日：2018-12-20

    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

    Inventor： Rui Wang ,  Jun Yin ,  Yong Kun Li ,  Wei Chen

    IPC: G06F16/50 ,  G06F16/901 ,  G06F16/28 ,  G06F30/18 ,  G06F16/00 ,  G06Q50/00 ,  G06Q30/02

    Abstract: A graph centrality determining method includes sampling, at least twice, nodes that are sequentially-connected and connection edges between the nodes, in an original graph representing a network structure, to obtain sampled sub-graphs, determining an influence of each of nodes in the sampled sub-graphs, forming a graph centrality determining result of each of the sampled sub-graphs, based on the influence of each of the nodes in the sampled sub-graphs, determining result of each of the sampled sub-graphs, to the original graph, to obtain an influence of each of the nodes in the original graph, clustering the influence of each of the nodes in the original graph, sorting the influence of each of the nodes in the original graph in descending order of a result of the clustering, and obtaining a predetermined quantity of nodes having influences that are top-ranked, in the original graph.

    BORDER DETECTION METHOD, SERVER AND STORAGE MEDIUM
    4.
    发明申请
    BORDER DETECTION METHOD, SERVER AND STORAGE MEDIUM 审中-公开

    公开(公告)号：US20200020105A1

    公开(公告)日：2020-01-16

    申请号：US16578672

    申请日：2019-09-23

    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

    Inventor： Xing SUN ,  Rui Wang ,  Xiaowei Guo

    IPC: G06T7/13 ,  G06K9/62

    Abstract: Provided is a border detection method, server, and storage medium. The method including detecting a plurality of first straight line segments in a to-be-detected image, the to-be-detected image comprising a target region of a to-be-determined border; generating a plurality of first candidate borders of the target region according to the plurality of first straight line segments; obtaining a plurality of second candidate borders of the target region from the plurality of first candidate borders; extracting border features of the plurality of second candidate borders; and obtaining an actual border of the target region from the plurality of second candidate borders according to the border features of the plurality of second candidate borders and a border detection model, the border detection model being used to determine a detected value of each candidate border, and the detected value representing a similarity between each candidate border and the actual border.

    Object recognition method and device, and storage medium
    5.
    发明授权
    Object recognition method and device, and storage medium 有权

    公开(公告)号：US11488302B2

    公开(公告)日：2022-11-01

    申请号：US16985966

    申请日：2020-08-05

    Applicant: Tencent Technology (Shenzhen) Company Limited

    Inventor： Rui Wang ,  Xing Sun ,  Xiaowei Guo

    IPC: G06T7/11 ,  G06T7/00 ,  G06K9/62 ,  G06N3/08 ,  G06V10/44

    Abstract: An object recognition method is performed at an electronic device. The method includes: pre-processing a target image, to obtain a pre-processed image, the pre-processed image including three-dimensional image information of a target region of a to-be-detected object, processing the pre-processed image by using a target data model, to obtain a target probability, the target probability being used for representing a probability that an abnormality appears in a target object in the target region of the to-be-detected object; and determining a recognition result of the target region of the to-be-detected object according to the target probability, the recognition result being used for indicating the probability that the abnormality appears in the target region of the to-be-detected object. The object recognition method can effectively improve accuracy of object recognition and avoid a case of incorrect recognition.

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