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    AUTOMATED IMAGE RETRIEVAL WITH IMAGE GRAPH
    2.
    发明申请
    AUTOMATED IMAGE RETRIEVAL WITH IMAGE GRAPH 审中-公开

    公开(公告)号：US20200159766A1

    公开(公告)日：2020-05-21

    申请号：US16592006

    申请日：2019-10-03

    Applicant: THE TORONTO-DOMINION BANK

    Inventor： Maksims Volkovs ,  Cheng Chang ,  Guangwei Yu ,  Chundi Liu

    IPC: G06F16/583 ,  G06F16/903 ,  G06F16/9032 ,  G06F16/901 ,  G06F16/58

    Abstract: An image retrieval system receives an image for which to identify relevant images from an image repository. Relevant images may be of the same environment or object and features and other characteristics. Images in the repository are represented in an image retrieval graph by a set of image nodes connected by edges to other related image nodes with edge weights representing the similarity of the nodes to each other. Based on the received image, the image traversal system identifies an image in the image retrieval graph and alternatively explores and traverses (also termed “exploits”) the image nodes with the edge weights. In the exploration step, image nodes in an exploration set are evaluated to identify connected nodes that are added to a traversal set of image nodes. In the traversal step, the relevant nodes in the traversal set are added to the exploration set and a query result set.

    Automated image retrieval with graph neural network
    3.
    发明授权
    Automated image retrieval with graph neural network 有权

    公开(公告)号：US11475059B2

    公开(公告)日：2022-10-18

    申请号：US16917422

    申请日：2020-06-30

    Applicant: THE TORONTO-DOMINION BANK

    Inventor： Chundi Liu ,  Guangwei Yu ,  Maksims Volkovs

    IPC: G06F16/58 ,  G06N3/08 ,  G06N3/04

    Abstract: A content retrieval system uses a graph neural network architecture to determine images relevant to an image designated in a query. The graph neural network learns a new descriptor space that can be used to map images in the repository to image descriptors and the query image to a query descriptor. The image descriptors characterize the images in the repository as vectors in the descriptor space, and the query descriptor characterizes the query image as a vector in the descriptor space. The content retrieval system obtains the query result by identifying a set of relevant images associated with image descriptors having above a similarity threshold with the query descriptor.

    AUTOMATED IMAGE RETRIEVAL WITH IMAGE GRAPH
    4.
    发明申请
    AUTOMATED IMAGE RETRIEVAL WITH IMAGE GRAPH 有权

    公开(公告)号：US20220318298A1

    公开(公告)日：2022-10-06

    申请号：US17848122

    申请日：2022-06-23

    Applicant: THE TORONTO-DOMINION BANK

    Inventor： Maksims Volkovs ,  Cheng Chang ,  Guangwei Yu ,  Chundi Liu

    IPC: G06F16/583 ,  G06F16/903 ,  G06F16/58 ,  G06F16/901 ,  G06F16/9032

    Abstract: An image retrieval system receives an image for which to identify relevant images from an image repository. Relevant images may be of the same environment or object and features and other characteristics. Images in the repository are represented in an image retrieval graph by a set of image nodes connected by edges to other related image nodes with edge weights representing the similarity of the nodes to each other. Based on the received image, the image traversal system identifies an image in the image retrieval graph and alternatively explores and traverses (also termed “exploits”) the image nodes with the edge weights. In the exploration step, image nodes in an exploration set are evaluated to identify connected nodes that are added to a traversal set of image nodes. In the traversal step, the relevant nodes in the traversal set are added to the exploration set and a query result set.

    AUTOMATED IMAGE RETRIEVAL WITH GRAPH NEURAL NETWORK
    5.
    发明申请
    AUTOMATED IMAGE RETRIEVAL WITH GRAPH NEURAL NETWORK 有权

    公开(公告)号：US20210049202A1

    公开(公告)日：2021-02-18

    申请号：US16917422

    申请日：2020-06-30

    Applicant: THE TORONTO-DOMINION BANK

    Inventor： Chundi Liu ,  Guangwei Yu ,  Maksims Volkovs

    IPC: G06F16/58 ,  G06N3/04 ,  G06N3/08

    Abstract: A content retrieval system uses a graph neural network architecture to determine images relevant to an image designated in a query. The graph neural network learns a new descriptor space that can be used to map images in the repository to image descriptors and the query image to a query descriptor. The image descriptors characterize the images in the repository as vectors in the descriptor space, and the query descriptor characterizes the query image as a vector in the descriptor space. The content retrieval system obtains the query result by identifying a set of relevant images associated with image descriptors having above a similarity threshold with the query descriptor.

    Automated image retrieval with graph neural network
    9.
    发明授权
    Automated image retrieval with graph neural network 有权

    公开(公告)号：US11809486B2

    公开(公告)日：2023-11-07

    申请号：US17900530

    申请日：2022-08-31

    Applicant: THE TORONTO-DOMINION BANK

    Inventor： Chundi Liu ,  Guangwei Yu ,  Maksims Volkovs

    IPC: G06F16/58 ,  G06N3/08 ,  G06N3/04

    CPC classification number: G06F16/58 ,  G06N3/04 ,  G06N3/08

    Abstract: A content retrieval system uses a graph neural network architecture to determine images relevant to an image designated in a query. The graph neural network learns a new descriptor space that can be used to map images in the repository to image descriptors and the query image to a query descriptor. The image descriptors characterize the images in the repository as vectors in the descriptor space, and the query descriptor characterizes the query image as a vector in the descriptor space. The content retrieval system obtains the query result by identifying a set of relevant images associated with image descriptors having above a similarity threshold with the query descriptor.

    AUTOMATED IMAGE RETRIEVAL WITH GRAPH NEURAL NETWORK
    10.
    发明申请
    AUTOMATED IMAGE RETRIEVAL WITH GRAPH NEURAL NETWORK 有权

    公开(公告)号：US20220414145A1

    公开(公告)日：2022-12-29

    申请号：US17900530

    申请日：2022-08-31

    Applicant: THE TORONTO-DOMINION BANK

    Inventor： Chundi Liu ,  Guangwei Yu ,  Maksims Volkovs

    IPC: G06F16/58 ,  G06N3/08 ,  G06N3/04

    Abstract: A content retrieval system uses a graph neural network architecture to determine images relevant to an image designated in a query. The graph neural network learns a new descriptor space that can be used to map images in the repository to image descriptors and the query image to a query descriptor. The image descriptors characterize the images in the repository as vectors in the descriptor space, and the query descriptor characterizes the query image as a vector in the descriptor space. The content retrieval system obtains the query result by identifying a set of relevant images associated with image descriptors having above a similarity threshold with the query descriptor.

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