EXPANDING INDEXED TERMS FOR SEARCHING FILES
    1.
    发明申请

    公开(公告)号:US20200004836A1

    公开(公告)日:2020-01-02

    申请号:US16147444

    申请日:2018-09-28

    Applicant: Apple Inc.

    Abstract: A device implementing a system for expanded search includes a processor configured to identify plural words, and generate, for each word of the plural words, a word vector based on a proximity of the word relative to other words of the plural words, the word vector comprising plural dimensions. The processor is further configured to create a compressed word vector structure comprising clusters of subsets of the plural dimensions across the word vectors, each cluster including similar values of the respective dimensions, convert the word vectors to points on at least one plane, and partition the at least one plane into nested groupings of the points based on a threshold number of points per nested grouping. The processor is further configured to create a tree look-up structure of the nested groupings, and provide the compressed word vector structure and the tree look-up structure to a client device.

    ADAPTIVE SUGGESTIONS FOR STICKERS

    公开(公告)号:US20240403354A1

    公开(公告)日:2024-12-05

    申请号:US18381105

    申请日:2023-10-17

    Applicant: Apple Inc.

    Abstract: The subject system may be implemented by at least one processor configured to obtain text input and select an image based on a comparison between the text input and a tag associated with the image. The tag was derived from at least one of the image or a prior use of the image, and the image was extracted from another image. The at least one processor is also configured to provide, responsive to obtaining the text input, the image.

    INTERACTIVE IMAGE SEGMENTATION
    6.
    发明申请

    公开(公告)号:US20210358127A1

    公开(公告)日:2021-11-18

    申请号:US17078086

    申请日:2020-10-22

    Applicant: Apple Inc.

    Abstract: A first subset of pixels of an image may be labeled with an object identifier based on user interactions with the image. Pixel data representing the pixels of the image may be passed through an embedding neural network model to generate pixel embedding vectors. A prototype embedding vector associated with the object identifier may be generated based pixel embedding vectors corresponding to the first subset of pixels. For each pixel of a second subset of pixels of the image, a probability that the pixel should be labeled with the object identifier may be determined based on the prototype embedding vector and pixel embedding vectors corresponding to the second subset of pixels. Pixels of the second subset of pixels may be labeled with the object identifier based on the determined probabilities, and the pixels in the image may be segmented based on the pixels labeled with the object identifier.

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