System and method for associating a successful second transaction with a first failed transaction

    公开(公告)号:US11941589B2

    公开(公告)日:2024-03-26

    申请号:US17711151

    申请日:2022-04-01

    Applicant: SHOPIFY INC.

    CPC classification number: G06Q20/02 G06Q30/0633 G06Q30/0641

    Abstract: Systems and methods for processing transactions are provided. An aspect of the transactions is executed with a third party transaction service provider that may indicate its aspect of the transaction was a failure when in fact it was successful. After conveying this failure to a user, the system subsequently learns that the aspect of the transaction was not a failure. The system attempts to associate such a transaction with another transaction based on a comparison between the transactions. Upon determining that there is an association between the second transaction and the first transaction, the system communicates to a user options for how to proceed with the first and second transactions. One of the options is to proceed with the original transaction. If the original transaction goes ahead, this saves system resources associated with cancelling the first transaction.

    Method and system for generating images using generative adversarial networks (GANs)

    公开(公告)号:US12243133B2

    公开(公告)日:2025-03-04

    申请号:US17734938

    申请日:2022-05-02

    Applicant: SHOPIFY INC.

    Abstract: An image processing method and system that generates output images. The system receives a first input image depicting a first set of products and determines the first set of products and corresponding first product categories. The system then receives, on a user interface of a requestor device, a second input image depicting other products selected as being of interest having corresponding second product categories for the other products. In response to a match between one of the first product categories and the second product categories: the system applies the first input image and the second input image to generative adversarial networks (GANs). Each GAN is trained using image dataset for corresponding ones of the first and second product categories, to generate an output image replacing at least a portion of first input image with the second input image, the replacement based on the match between the product categories.

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