CLUSTERING IMAGES FOR ANOMALY DETECTION
    2.
    发明申请

    公开(公告)号:WO2023086909A1

    公开(公告)日:2023-05-19

    申请号:PCT/US2022/079674

    申请日:2022-11-10

    Applicant: GOOGLE LLC

    Abstract: A computer-implemented method (500) includes receiving an anomaly clustering request (20) that requests data processing hardware (144) to assign each image (152) of a plurality of images into one of a plurality of groups (302). The method also includes obtaining a plurality of images. For each respective image, the method includes extracting a respective set of patch embeddings (212) from the respective image, determining a distance (212) between the respective set of patch embeddings and each other set of patch embeddings, and assigning the respective image into one of the plurality of groups using the distances between the respective set of patch embeddings and each other set of patch embeddings.

    LATE MATERIALIZATION OF QUERIED DATA IN DATABASE CACHE

    公开(公告)号:WO2023086322A1

    公开(公告)日:2023-05-19

    申请号:PCT/US2022/049235

    申请日:2022-11-08

    Applicant: GOOGLE LLC

    Abstract: Aspects of the disclosure are directed to late materialization of attributes in response to queries to a database implementing a database cache. Queried data is materialized in temporary memory before the data is projected as part of generating a result to the query. Instead of materializing all of the attributes referenced in a query before executing the query, a database management system materializes attributes as "late" as possible—when the operation needing the attributes is executed. The operation needing the attributes can be performed sooner, as opposed to materializing all referenced attributes are materialized before executing the query.

    METHODS AND SYSTEMS FOR PRESENTING MEDIA CONTENT WITH MULTIPLE MEDIA ELEMENTS IN AN EDITING ENVIRONMENT

    公开(公告)号:WO2023086091A1

    公开(公告)日:2023-05-19

    申请号:PCT/US2021/058940

    申请日:2021-11-11

    Applicant: GOOGLE LLC

    Abstract: Methods, systems, and media for presenting media content with multiple media elements in an editing environment are provided. In some embodiments, the method comprises: receiving, using a computing device having a display, a request to modify a video content item containing a plurality of media elements; presenting a user interface that includes a video track representation of the video content item and a layered representation of the plurality of media elements occurring within the video content item, wherein each of the plurality of media elements is represented by a media overlay element that is positioned proximal to the video track representation and wherein the media overlay element has one or more visual characteristics; in response to receiving a selected time position within the video track representation, updating the layered representation within the user interface to present an expanded overlay list that includes media overlay elements corresponding to the subset of the plurality of media elements that occur at the selected time position within the video content item; and, in response to receiving a selected media overlay element from the expanded overlay list, updating a media window in the user interface to present a video frame corresponding to the selected time position and the media element applied to the video frame corresponding to the selected media overlay element.

    CONTEXT-AIDED IDENTIFICATION
    5.
    发明申请

    公开(公告)号:WO2023081605A1

    公开(公告)日:2023-05-11

    申请号:PCT/US2022/078893

    申请日:2022-10-28

    Applicant: GOOGLE LLC

    Abstract: Smart devices can be configured to collect and share various forms of context data about where a user is located (e.g., location), what a user will be doing (e.g., schedule), and what a user is currently doing (e.g., activity). This context data may be combined with fingerprint data (e.g., biometrics) to help identify the fingerprint data. For example, a location of a user may help associated speech detected at that location with the user. These associations may be stored in a mapping database that can be updated over time to reduce ambiguities in identification. The mappings in the database may be used to train a machine learning model to recognize fingerprints as identities, which may be useful in applications, such as speaker identification.

    MANAGING DATA AVAILABILITY ON ENCRYPTION KEY STATUS CHANGES IN REPLICATED STORAGE SYSTEMS

    公开(公告)号:WO2023077062A1

    公开(公告)日:2023-05-04

    申请号:PCT/US2022/078864

    申请日:2022-10-28

    Applicant: GOOGLE LLC

    Abstract: A method (300) includes obtaining a key status (164) for a first cryptographic key (162). The first cryptographic key is used to encrypt replicated data (22) of a first replication instance (172). The method also includes determining, based on the key status, that the first cryptographic key is inaccessible which causes the first replication instance to be unavailable. In response to determining that the first cryptographic key is inaccessible, the method includes scheduling a second replication instance to be unavailable after a threshold amount of time has passed. The second replication instance includes replicated data encrypted by a second cryptographic key that is accessible. After the threshold amount of time has passed and when the first cryptographic key is still inaccessible, the method includes setting the second replication instance as unavailable.

    MACHINE LEARNING TECHNIQUES FOR USER GROUP BASED CONTENT DISTRIBUTION

    公开(公告)号:WO2023075774A1

    公开(公告)日:2023-05-04

    申请号:PCT/US2021/057028

    申请日:2021-10-28

    Applicant: GOOGLE LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training and using machine learning models. In some aspects, a method includes identifying a first set of data for users of multiple user groups. For each user, a first party user identifier is obtained that identifies the individual user to a first party content provider. A second set of data describing activity of the user with respect to content of the first party content provider is identified. For each user, a contextual analysis of the first set and the second set of data is performed to generate one or more labels indicating user interest. A training dataset is generated based on the first set and the second set of data and a label. The training dataset is then used to train one or more machine learning models to predict user interest.

    EFFICIENTLY PERFORMING INFERENCE COMPUTATIONS OF A FULLY CONVOLUTIONAL NETWORK FOR INPUTS WITH DIFFERENT SIZES

    公开(公告)号:WO2023075742A1

    公开(公告)日:2023-05-04

    申请号:PCT/US2021/056418

    申请日:2021-10-25

    Applicant: GOOGLE LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing inference computations of a fully convolutional neural network receiving inputs with different sizes. One of the methods include receiving a new input to be processed by a fully convolutional neural network, the new input having a first size different from a fixed size that the fully convolutional neural network is configured to process; determining, one or more fixed-size inputs from the new input, each fixed-size input having the fixed size; obtaining a respective fixed-size output generated by the fully convolutional neural network performing inference computations for each of the one or more fixed-size inputs; and generating, from the respective fixed-size outputs comprising one or more invalid pixel values, a final output that is equivalent to an output that would be generated by processing the new input using the fully convolutional neural network.

Patent Agency Ranking