Systems and methods for automatic image generation and arrangement using a machine learning architecture

    公开(公告)号:US12277749B1

    公开(公告)日:2025-04-15

    申请号:US18943693

    申请日:2024-11-11

    Abstract: A method includes receiving a first image; extracting a first set of features from the first image; executing a first machine learning model using the extracted first set of features as input to generate a first image performance score for the first image; iteratively executing, using the first set of features as input for each execution, a generative machine learning model to generate a plurality of generated images; extracting a second set of features from each of the plurality of generated images; iteratively executing the first machine learning model using a different second set of features as input for each execution to generate a generated image performance score for each of the plurality of generated images; and transmitting a defined number of the plurality of generated images to a computing device, the defined number of generated images determined based on the generated image performance scores.

    Systems and methods for using image scoring for an improved search engine

    公开(公告)号:US12249118B2

    公开(公告)日:2025-03-11

    申请号:US18916516

    申请日:2024-10-15

    Abstract: A method includes storing at least one image performance score for each of a set of images, the set of images comprising a plurality of subsets of images, each subset corresponding with a different web page of a plurality of web pages, the at least one image performance score for an image indicating a likelihood that a user will interact with the image; determining a web page score for each of the plurality of web pages based on one or more image performance scores of the subset of images that corresponds with the web page; receiving a query comprising one or more keywords or images; selecting a set of web pages by applying a search engine machine learning model to the one or more keywords and the web page score for each of the plurality of web pages; and presenting the set of web pages at a computing device.

    SYSTEMS AND METHODS FOR TRAINING A MULTI-MODAL MACHINE LEARNING ARCHITECTURE FOR CONTENT GENERATION

    公开(公告)号:US20250078453A1

    公开(公告)日:2025-03-06

    申请号:US18948425

    申请日:2024-11-14

    Abstract: The present disclosure describes a method comprising receiving a plurality of training images; executing a feature extraction machine learning model to generate a plurality of training embeddings for a plurality of training images each in an embedding space; training a content scoring machine learning model using the plurality of training embeddings to generate performance scores for content items based on embeddings in the embedding space; receiving a set of text; executing the feature extraction machine learning model using the set of text to generate a text embedding in the same embedding space as the training embeddings for the plurality of training images; generating, using the content scoring machine learning model, a text performance score for the set of text using the text embedding in the embedding space; and generating a record identifying the text performance score for the set of text.

    SYSTEMS AND METHODS FOR USING IMAGE SCORING FOR AN IMPROVED SEARCH ENGINE

    公开(公告)号:US20240303965A1

    公开(公告)日:2024-09-12

    申请号:US18664173

    申请日:2024-05-14

    CPC classification number: G06V10/761 G06F16/438 G06N3/045 G06V10/40 G06V10/82

    Abstract: A method includes storing at least one image performance score for each of a set of images, the set of images comprising a plurality of subsets of images, each subset corresponding with a different web page of a plurality of web pages, the at least one image performance score for an image indicating a likelihood that a user will interact with the image; determining a web page score for each of the plurality of web pages based on one or more image performance scores of the subset of images that corresponds with the web page; receiving a query comprising one or more keywords or images; selecting a set of web pages by applying a search engine machine learning model to the one or more keywords and the web page score for each of the plurality of web pages; and presenting the set of web pages at a computing device.

    SYSTEMS AND METHODS FOR AUTOMATING BENCHMARK GENERATION USING NEURAL NETWORKS FOR IMAGE OR VIDEO SELECTION

    公开(公告)号:US20240257494A1

    公开(公告)日:2024-08-01

    申请号:US18592935

    申请日:2024-03-01

    CPC classification number: G06V10/761 G06F16/438 G06N3/045 G06V10/40 G06V10/82

    Abstract: A method includes accessing a web-based property over a network; storing a plurality of images or videos from the web-based property and associations between the plurality of images or videos and a target audience identifier responsive to the web-based property having a stored association with the target audience identifier; retrieving the plurality of images or videos from the database responsive to each of the plurality of images or videos having stored associations with the target audience identifier; executing a neural network to generate a performance score for each of the plurality of images or videos; calculating a target audience benchmark; executing the neural network to generate a first performance score for a first image or video and a second performance score for a second image or video; comparing the first performance score and the second performance score to the benchmark; and generating a record identifying the first image or video.

    Systems and methods for using image scoring an improved search engine

    公开(公告)号:US12020470B1

    公开(公告)日:2024-06-25

    申请号:US18433846

    申请日:2024-02-06

    CPC classification number: G06V10/761 G06F16/438 G06N3/045 G06V10/40 G06V10/82

    Abstract: A method includes storing at least one image performance score for each of a set of images, the set of images comprising a plurality of subsets of images, each subset corresponding with a different web page of a plurality of web pages, the at least one image performance score for an image indicating a likelihood that a user will interact with the image; determining a web page score for each of the plurality of web pages based on one or more image performance scores of the subset of images that corresponds with the web page; receiving a query comprising one or more keywords or images; selecting a set of web pages by applying a search engine machine learning model to the one or more keywords and the web page score for each of the plurality of web pages; and presenting the set of web pages at a computing device.

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