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    LEARNING UNIFIED EMBEDDING
    42.
    发明申请
    LEARNING UNIFIED EMBEDDING 审中-公开

    公开(公告)号：US20200090039A1

    公开(公告)日：2020-03-19

    申请号：US16494842

    申请日：2017-11-17

    Applicant: Google LLC

    Inventor： Yang Song ,  Yuan Li ,  Bo Wu ,  Chao-Yeh Chen ,  Xiao Zhang ,  Hartwig Adam

    IPC: G06N3/08 ,  G06N20/00 ,  G06K9/32

    Abstract: A computer-implemented method for generating a unified machine learning model using a neural network on a data processing apparatus is described. The method includes the data processing apparatus determining respective learning targets for each of a plurality of object verticals. The data processing apparatus determines the respective learning targets based on two or more embedding outputs of the neural network. The method also includes the data processing apparatus training the neural network to identify data associated with each of the plurality of object verticals. The data processing apparatus trains the neural network using the respective learning targets and based on a first loss function. The data processing apparatus uses the neural network trained to generate a unified machine learning model, where the model is configured to identify particular data items associated with each of the plurality of object verticals.

    System and method for associating images with semantic entities
    49.
    发明授权
    System and method for associating images with semantic entities 有权

    公开(公告)号：US10268703B1

    公开(公告)日：2019-04-23

    申请号：US15372568

    申请日：2016-12-08

    Applicant: Google LLC

    Inventor： Maks Ovsjanikov ,  Yuan Li ,  Hartwig Adam ,  Charles Joseph Rosenberg

    IPC: G06F17/30

    Abstract: A system and computer-implemented method for associating images with semantic entities and providing search results using the semantic entities. An image database contains one or more source images associated with one or more images labels. A computer may generate one or more documents containing the labels associated with each image. Analysis may be performed on the one or more documents to associate the source images with semantic entities. The semantic entities may be used to provide search results. In response to receiving a target image as a search query, the target image may be compared with the source images to identify similar images. The semantic entities associated with the similar images may be used to determine a semantic entity for the target image. The semantic entity for the target image may be used to provide search results in response to the search initiated by the target image.

    Facial Recognition With Social Network Aiding
    50.
    发明申请
    Facial Recognition With Social Network Aiding 审中-公开

    公开(公告)号：US20180322147A1

    公开(公告)日：2018-11-08

    申请号：US16030316

    申请日：2018-07-09

    Applicant: Google LLC

    Inventor： David Petrou ,  Andrew Rabinovich ,  Hartwig Adam

    IPC: G06F17/30 ,  G06K9/00

    CPC classification number: G06F16/5866 ,  G06F16/24578 ,  G06F16/532 ,  G06F16/5838 ,  G06F16/9535 ,  G06K9/00288 ,  G06K9/00677

    Abstract: A facial recognition search system identifies one or more likely names (or other personal identifiers) corresponding to the facial image(s) in a query as follows. After receiving the visual query with one or more facial images, the system identifies images that potentially match the respective facial image in accordance with visual similarity criteria. Then one or more persons associated with the potential images are identified. For each identified person, person-specific data comprising metrics of social connectivity to the requester are retrieved from a plurality of applications such as communications applications, social networking applications, calendar applications, and collaborative applications. An ordered list of persons is then generated by ranking the identified persons in accordance with at least metrics of visual similarity between the respective facial image and the potential image matches and with the social connection metrics. Finally, at least one person identifier from the list is sent to the requester.

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