TAG DISTRIBUTION VISUALIZATION SYSTEM
    2.
    发明公开

    公开(公告)号:US20240256595A1

    公开(公告)日:2024-08-01

    申请号:US18633132

    申请日:2024-04-11

    Applicant: Snap Inc.

    Abstract: In various embodiments described herein, a visualization system receives message requests from client devices, wherein the message requests comprise at least location data that identifies a location of a client device, and media content, wherein the media content includes at least one of image data, audio data, and video data. In response to receiving the message requests that comprise the media content, the visualization system analyzes and parses the media content to detect one or more tags embedded within the media content. In response to detecting the tag, the visualization system identifies a campaign or account referenced by or associated with the tag. Based on the identification of the campaign based on the tag within the media content, the visualization system determines a distribution of the campaign based on the location data from the message request.

    Tag distribution visualization system

    公开(公告)号:US11983215B2

    公开(公告)日:2024-05-14

    申请号:US17936277

    申请日:2022-09-28

    Applicant: Snap Inc.

    Abstract: In various embodiments described herein, a visualization system receives message requests from client devices, wherein the message requests comprise at least location data that identifies a location of a client device, and media content, wherein the media content includes at least one of image data, audio data, and video data. In response to receiving the message requests that comprise the media content, the visualization system analyzes and parses the media content to detect one or more tags embedded within the media content. In response to detecting the tag, the visualization system identifies a campaign or account referenced by or associated with the tag. Based on the identification of the campaign based on the tag within the media content, the visualization system determines a distribution of the campaign based on the location data from the message request.

    Machine learned single image icon identification

    公开(公告)号:US11676019B2

    公开(公告)日:2023-06-13

    申请号:US17661868

    申请日:2022-05-03

    Applicant: Snap Inc.

    CPC classification number: G06N3/08 G06F18/22 G06N20/00 G06V10/751 G06V20/10

    Abstract: Systems, devices, media, and methods are presented for graphical icon identification within an image or video stream. The systems and methods receive an image including a graphical icon. The systems and methods identify a set of proposed regions of the image, at least one proposed region of the set of proposed regions containing the graphical icon and extract a set of semantic features for each proposed region of the set of proposed regions. Based on the set of semantic features of the set of proposed regions, the systems and methods identify a set of proposed icons corresponding to the graphical icon included in the image and determine a match between the graphical icon and at least one proposed icon of the set of proposed icons.

    MACHINE LEARNED SINGLE IMAGE ICON IDENTIFICATION

    公开(公告)号:US20210192259A1

    公开(公告)日:2021-06-24

    申请号:US17249499

    申请日:2021-03-03

    Applicant: Snap Inc.

    Abstract: Systems, devices, media, and methods are presented for graphical icon identification within an image or video stream. The systems and methods receive an image including a graphical icon. The systems and methods identify a set of proposed regions of the image, at least one proposed region of the set of proposed regions containing the graphical icon and extract a set of semantic features for each proposed region of the set of proposed regions. Based on the set of semantic features of the set of proposed regions, the systems and methods identify a set of proposed icons corresponding to the graphical icon included in the image and determine a match between the graphical icon and at least one proposed icon of the set of proposed icons.

    MACHINE LEARNED SINGLE IMAGE ICON IDENTIFICATION

    公开(公告)号:US20220262092A1

    公开(公告)日:2022-08-18

    申请号:US17661868

    申请日:2022-05-03

    Applicant: Snap Inc.

    Abstract: Systems, devices, media, and methods are presented for graphical icon identification within an image or video stream. The systems and methods receive an image including a graphical icon. The systems and methods identify a set of proposed regions of the image, at least one proposed region of the set of proposed regions containing the graphical icon and extract a set of semantic features for each proposed region of the set of proposed regions. Based on the set of semantic features of the set of proposed regions, the systems and methods identify a set of proposed icons corresponding to the graphical icon included in the image and determine a match between the graphical icon and at least one proposed icon of the set of proposed icons.

    CONTENT TAGGING
    7.
    发明申请

    公开(公告)号:US20210216830A1

    公开(公告)日:2021-07-15

    申请号:US17248386

    申请日:2021-01-22

    Applicant: SNAP INC.

    Abstract: Systems, methods, devices, media, and computer readable instructions are described for local image tagging in a resource constrained environment. One embodiment involves processing image data using a deep convolutional neural network (DCNN) comprising at least a first subgraph and a second subgraph, the first subgraph comprising at least a first layer and a second layer, processing, the image data using at least the first layer of the first subgraph to generate first intermediate output data; processing, by the mobile device, the first intermediate output data using at least the second layer of the first subgraph to generate first subgraph output data, and in response to a determination that each layer reliant on the first intermediate data have completed processing, deleting the first intermediate data from the mobile device. Additional embodiments involve convolving entire pixel resolutions of the image data against kernels in different layers if the DCNN.

    Content tagging
    8.
    发明授权

    公开(公告)号:US10956793B1

    公开(公告)日:2021-03-23

    申请号:US16192419

    申请日:2018-11-15

    Applicant: Snap Inc.

    Abstract: Systems, methods, devices, media, and computer readable instructions are described for local image tagging in a resource constrained environment. One embodiment involves processing image data using a deep convolutional neural network (DCNN) comprising at least a first subgraph and a second subgraph, the first subgraph comprising at least a first layer and a second layer, processing, the image data using at least the first layer of the first subgraph to generate first intermediate output data; processing, by the mobile device, the first intermediate output data using at least the second layer of the first subgraph to generate first subgraph output data, and in response to a determination that each layer reliant on the first intermediate data have completed processing, deleting the first intermediate data from the mobile device. Additional embodiments involve convolving entire pixel resolutions of the image data against kernels in different layers if the DCNN.

    TAG DISTRIBUTION VISUALIZATION SYSTEM
    10.
    发明申请

    公开(公告)号:US20190205430A1

    公开(公告)日:2019-07-04

    申请号:US15860847

    申请日:2018-01-03

    Applicant: Snap Inc.

    Abstract: In various embodiments described herein, a visualization system receives message requests from client devices, wherein the message requests comprise at least location data that identifies a location of a client device, and media content, wherein the media content includes at least one of image data, audio data, and video data. In response to receiving the message requests that comprise the media content, the visualization system analyzes and parses the media content to detect one or more tags embedded within the media content. In response to detecting the tag, the visualization system identifies a campaign or account referenced by or associated with the tag. Based on the identification of the campaign based on the tag within the media content, the visualization system determines a distribution of the campaign based on the location data from the message request.

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