Systems and methods of generating color palettes with a generative adversarial network

    公开(公告)号:US11373343B2

    公开(公告)日:2022-06-28

    申请号:US17091259

    申请日:2020-11-06

    Abstract: Generating, at a server of a generative adversarial network (GAN) for color selection, a training set of color palettes. A color palette generator of the server generates a first set of color palettes based on the training set of color palettes. The first set of color palettes may be compared with a reference set of color palettes to predict a curated set of color palettes. Colors from the curated set of color palettes may be removed that are within a predetermined distance from one another in a color space. The GAN may be validated by performing cluster analysis to determine outlier latent dimensions to be changed for the color selection by the GAN. Proposed color palettes may be generated based on the GAN to be displayed on a display device.

    SYSTEMS AND METHODS OF GENERATING COLOR PALETTES WITH A GENERATIVE ADVERSARIAL NETWORK

    公开(公告)号:US20220148232A1

    公开(公告)日:2022-05-12

    申请号:US17091259

    申请日:2020-11-06

    Abstract: Systems and method are provided for generating, at a server of a generative adversarial network (GAN) for color selection, a training set of color palettes. A color palette generator of the server generates a first set of color palettes based on the training set of color palettes. The first set of color palettes may be compared with a reference set of color palettes to predict a curated set of color palettes. Colors from the curated set of color palettes may be removed that are within a predetermined distance from one another in a color space. The GAN may be validated by performing cluster analysis to determine outlier latent dimensions to be changed for the color selection by the GAN. Proposed color palettes may be generated based on the GAN to be displayed on a display device.

    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.

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