Abstract: Systems and methods for frequency management, including: an online media service configured to: receive a request for a media item, the request including a recipient identifier; identify a set of candidate media items ranked by a set of matching criteria; a frequency management service configured to: perform a query against a lookup service, where the query includes (i) an entity identifier of at least one candidate media item of the set of candidate media items, and (ii) the recipient identifier; receive a response from the lookup service including a quantity of impressions associated with the entity identifier and the recipient identifier; identify a predefined frequency threshold; determine that the frequency threshold is exceeded and exclude the at least one candidate media item from a result set based on the determination; and provide the result set including an identifier of at least one other candidate media item.

Abstract: Systems and methods for frequency management, including: an online media service configured to: receive a request for a media item, the request including a recipient identifier; identify a set of candidate media items ranked by a set of matching criteria; a frequency management service configured to: perform a query against a lookup service, where the query includes (i) an entity identifier of at least one candidate media item of the set of candidate media items, and (ii) the recipient identifier; receive a response from the lookup service including a quantity of impressions associated with the entity identifier and the recipient identifier; identify a predefined frequency threshold; determine that the frequency threshold is exceeded and exclude the at least one candidate media item from a result set based on the determination; and provide the result set including an identifier of at least one other candidate media item.

Abstract: Systems and methods for programmatic generation of training data, including: a training data generation engine configured to: identify an image asset corresponding to an entity; identify a training video; select a consecutive subset of frames of the training video based on a procedure for ranking frames on their candidacy for overlaying content; for at least one frame of the subset of frames: perform an augmentation technique on the identified logo image to generate an augmented image asset; overlay at least one variation of the image asset, including the augmented image asset, onto each of the subset of frames to generate a set of overlayed frames; and generate an augmented version of the training video including the overlayed frames; and a model training engine configured to: train an artificial intelligence model for entity detection using the augmented version of the training video.

Abstract: Systems and methods for entity detection using artificial intelligence, including: a deep learning model service configured to: select and analyze a set of frames from a media item to determine a set of candidate brand-probability pairs; a voting engine configured to: determining that a first brand-probability pair of a set of candidate brand-probability pairs based on at least one obtained hyperparameter value does not meet a threshold for determining whether candidate brand-probability pairs are to be included in a result set; excluding the first brand-probability pair from the result set based on the determination; sorting the result set; and selecting at least one final brand-probability pair from the result set; and an offline transcoding service configured to: store the final brand-probability pair in a repository with a relation to an identifier of the media item.