Clarifai, Inc.

David Joshua Eigen

Matthew Donald Zeiler

Christopher David Fox

Ryan F Compton

Methods and computer readable media for facilitating training of a recognition model. An embodiment includes generating media items based on information associated with a representation of a graphic, the information including content other than the graphic, content based on at least one transformation parameter set, and content comprising the graphic integrated with the other content, then using a recognition model to process the media items to generate predictions related to recognition of the graphic for the media items, the generated predictions including an indication of a predicted location of the graphic in a first media item. The process also includes presenting an indication of the predicted location on an area of the first media item via a user interface to a user, then obtaining a reference feedback set that includes reference indications related to recognition of the graphic for the media items and including user feedback concerning the indication of the predicted location of the graphic, and then updating the recognition model based on the reference feedback.

System and method for facilitating graphic-recognition training of a recognition model

In certain embodiments, training of a prediction model (e.g., recognition or other prediction model) may be facilitated via a training set based on one or more logos or other graphics. In some embodiments, graphics information associated with a logo or graphic (e.g., to be recognized via a recognition model) may be obtained. Media items (e.g., images, videos, etc.) may be generated based on the graphics information, where each of the media items includes (i) content other than the logo and (ii) a given representation of the logo integrated with the other content. In some embodiments, the media items may be processed via the recognition model to generate predictions (related to recognition of the logo or graphic for the media items). The recognition model may be updated based on (i) the generated predictions and (ii) corresponding reference indications (related to recognition of the logo for the media items).

In certain embodiments, content items may be obtained, where each of the content items may include multiple data types. Machine learning models may be caused to be trained based on the content items to map data in a vector space by providing at least a first portion of each of the content items as input to at least one of the machine learning models and providing at least a second portion of each of the content items as input to at least another one of the machine learning models. A search request for results may be obtained, where the search request includes search parameters. One or more locations within the vector space may be predicted (e.g., by one or more of the machine learning models) based on the search parameters. Information (indicating content items mapped to or proximate the predicted locations) may be provided as a request response.

Prediction-model-based mapping and/or search using a multi-data-type vector space

In certain embodiments, training of a prediction model (e.g., recognition or other prediction model) may be facilitated via a training set generated based on one or more logos or other graphics. In some embodiments, graphics information associated with a logo or graphic (e.g., to be recognized via a recognition model) may be obtained. Training media items (e.g., images, videos, etc.) may be generated based on the graphics information, where each of the training media items includes (i) content other than the logo and (ii) a given representation of the logo integrated with the other content. The training media items may be processed via the recognition model to generate predictions (related to recognition of the logo or graphic for the training media items). The recognition model may be updated based on (i) the generated predictions and (ii) corresponding reference indications (related to recognition of the logo for the training media items).

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New York, NY, United States of America

David Joshua Eigen