User interface design update automation

    公开(公告)号:US11954463B2

    公开(公告)日:2024-04-09

    申请号:US17512444

    申请日:2021-10-27

    CPC classification number: G06F8/38 G06F8/36 G06F40/30 G06N20/00

    Abstract: Techniques are disclosed relating to determining a similarity of components of a current webpage to different UI components for use in automatically generating an updated webpage. A computer system may receive information specifying a current webpage, including a particular current UI component and information specifying a plurality of different UI components for an updated webpage. The computer system may identify one or more characteristics of the particular current UI component. The computer system may determine, based on the identified one or more characteristics, a similarity of ones of the plurality of different UI components to the particular current UI component. The computer system may select, based on the determining, a particular different UI component from the plurality of different UI components for use, in the updated webpage, for the particular current UI component. Such techniques may advantageously improve user experience by automatically providing up-to-date user interfaces.

    Automatic Image Conversion
    4.
    发明申请

    公开(公告)号:US20230129240A1

    公开(公告)日:2023-04-27

    申请号:US17649045

    申请日:2022-01-26

    Abstract: Techniques are disclosed for automatically converting a layout image to a text-based representation. In the disclosed techniques, a server computer system receives a layout image that includes a plurality of portions representing a plurality of user interface (UI) elements included in a UI design. The server computer system transforms, via executed of a trained residual neural network (ResNet), the layout image to a text-based representation of the layout image that specifies coordinates of bounding regions of the plurality of UI elements included in the UI design, where the text-based representation is usable to generate program code executable to render the UI design. The disclosed techniques may advantageously automate one or more portions of a UI design process and, as a result save time and computing resources via the execution of an image to text-based conversion ResNet machine learning model.

    User interface migration using intermediate user interfaces

    公开(公告)号:US11537363B2

    公开(公告)日:2022-12-27

    申请号:US16778936

    申请日:2020-01-31

    Abstract: Techniques are disclosed relating to generating a user interface (UI) migration plan, including intermediate UIs, for migrating from a current UI to a new UI. A computer system may receive information specifying a current UI and a new UI, and identify one or more differences between the current and the new UIs. Based on the differences, the computer system may generate information specifying one or more candidate intermediate UIs. The computer system may score the candidate intermediate UIs relative to a specified set of design criteria. The computer system may determine a UI migration plan that specifies a set of the one or more candidate intermediate UIs that are displayable in order to migrate from the current UI to the new UI, where the set of one or more intermediate UIs is selected based on the scoring. Use of the UI migration plan may advantageously reduce user interaction issues.

    User interface design update automation

    公开(公告)号:US11182135B2

    公开(公告)日:2021-11-23

    申请号:US16779177

    申请日:2020-01-31

    Abstract: Techniques are disclosed relating to determining a similarity of components of a current user interface (UI) to new UI components for use in automatically generating a new UI. A computer system may receive information specifying a current UI including a particular current UI component and information specifying a plurality of new UI components for a new UI. The computer system may then identify characteristics of the particular current UI component. Based on these identified characteristics, the computer system may score ones of the plurality of new UI components, where the scoring is performed to determine a similarity to the particular current UI component. The computer system may then select, based on the scores, a particular new UI component from the plurality of new UI components for use, in the new UI, for the particular current UI component. Such techniques may advantageously improve user experience by automatically providing up-to-date user interfaces.

    USER INTERFACE MIGRATION USING INTERMEDIATE USER INTERFACES

    公开(公告)号:US20210240318A1

    公开(公告)日:2021-08-05

    申请号:US16778936

    申请日:2020-01-31

    Abstract: Techniques are disclosed relating to generating a user interface (UI) migration plan, including intermediate UIs, for migrating from a current UI to a new UI. A computer system may receive information specifying a current UI and a new UI, and identify one or more differences between the current and the new UIs. Based on the differences, the computer system may generate information specifying one or more candidate intermediate UIs. The computer system may score the candidate intermediate UIs relative to a specified set of design criteria. The computer system may determine a UI migration plan that specifies a set of the one or more candidate intermediate UIs that are displayable in order to migrate from the current UI to the new UI, where the set of one or more intermediate UIs is selected based on the scoring. Use of the UI migration plan may advantageously reduce user interaction issues.

    One-to-Many Automatic Content Generation

    公开(公告)号:US20230129431A1

    公开(公告)日:2023-04-27

    申请号:US17649016

    申请日:2022-01-26

    Abstract: Techniques are disclosed for automatically generating new content using a trained 1-to-N generative adversarial network (GAN) model. In disclosed techniques, a computer system receives, from a computing device, a request for newly-generated content, where the request includes current content. The computer system automatically generates, using the trained 1-to-N GAN model, N different versions of new content, where a given version of new content is automatically generated based on the current content and one of N different style codes, where the value of N is at least two. After generating the N different versions of new content, the computer system transmits them to the computing device. The disclosed techniques may advantageously automate a content generation process, thereby saving time and computing resources via execution of the 1-to-N GAN machine learning model.

Patent Agency Ranking