Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: analyzing a respective foreground of one or more related digital images to identify a respective skin region in the respective foreground of the one or more related digital images; when the respective skin region is not identified, analyzing the respective foreground of the one or more related digital images to identify a respective head region in the respective foreground; extracting one or more patches from respective non-head region remainders of the respective foreground; and coordinating displaying a patch of the one or more patches on an electronic display based on one or more scores for the one or more patches. Other embodiments are described herein.

Abstract: A system includes a processor and a non-transitory computer-readable medium storing computing instructions that, when executed, perform operations including tokenizing a query. Tokens are transformed into embeddings. The embeddings are passed through a classification layer, producing log its. A sigmoid function is applied to convert the log its into a probability vector for Part Terminology Identifiers (PTIDs) associated with one or more domains. The probability vector is filtered to retain PTIDs based on respective probabilities satisfying a threshold. A sum of the probabilities is a predetermined sum value. The PTIDs are ranked by their probabilities. Business logic is applied to the ranked PTIDs using a PTID Understanding Model to determine a final result output to a fitment service. The PTID Understanding Model is pretrained to trigger a fitment determination process and/or a query results filter process for the one or more domains when the final result is valid.

Abstract: Systems, apparatuses, and methods for determining item availability are provided. A computer implemented method for determining item availability in a shopping space comprising: receiving a request for an item for purchase, instructing a motorized transport unit to travel to a display space in the shopping space corresponding to the item for the purchase, determining whether the item is available in the display space based on information captured by one or more sensors of the motorized transport unit, and in an event that the item for purchase is not available in the display space: determining an item unavailable response to present to the customer.

Abstract: Examples a digital tag integration system using modular data to populate digital tags with item data. In some examples, a tag manager obtains a tag unique identifier (UID) for each digital tag associated with a modular display in accordance with a customized scan sequence. Each digital tag is temporarily matched to an item UID having the same position in an item placement sequence as the digital tag without requiring a user to scan the UID on the physical items. The temporary tag-item pairing can be undone while setting the modular is in-progress. When the number of tag-item pairs is equal to an expected number for a portion of the modular display, the digital tags are linked to the paired items. Linked digital tags are populated with item data for linked items. When the linked digital tag is reset, the digital tag is updated back to an initial unlinked state.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a search query from a user during a current user session; generating a query embedding for the search query; determining one or more entity embeddings with similarity scores that satisfy a threshold, the one or more entity embeddings including keywords associated with entities; filtering the one or more entity embeddings based on filtering criteria; generating a mapping for the search query based on the one or more entity embeddings, the mapping including an association between keywords in the search query and an entity; and modifying a graphical user interface to display items associated with the entity in an upper portion of the graphical user interface during the current user session. Other embodiments are disclosed herein.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to assessing items for sale. In some embodiments, there is provided a system for assessing items for sale at a retail facility including an imaging device, a database, and a control circuit. The control circuit configured to: receive a captured image of at least one of items for sale; receive, for each item in the captured image, an identification of the item for sale associated with each bounding box; map item dimensions for each identified item for sale to pixels associated with each bounding box in the captured image; determine a volume estimate corresponding to the at least one of the items for sale supported on a surface; and determine, based on at least the volume estimate and the item dimensions, a quantity of the at least one of the items for sale supported on the surface.

Abstract: A control circuit obtains a first set of rules that define a conveyability range for containers as a function of conveyability constraints pertaining to an intermediary distribution facility. The control circuit also accesses conveyability constraint information for the intermediary distribution facility and generates a conveyability range for that facility by evaluating the constraint information against the first set of rules. The control circuit obtains a second set of rules that define an objective function that uses the conveyability range as a constraint to determine an optimal container pack size for the given item. (By one approach these teachings will also accommodate using at least two additional constraints, such as a so-called days-of-supply (DOS) constraint and a so-called pack-and-a-half constraint.) The control circuit then generates an optimal container pack size for the given item by evaluating the objective function against the conveyability range (and other selected constraints).

Abstract: Example implementations may relate to systems and methods for re-ranking item recommendations. For example, a computer-implemented method may include receiving recommended items for items in a cart of an online checkout. The computer-implemented method can also include iteratively generating clusters of a pair of recommended item of the recommended items and a fulfillment center of the recommended item, and a pair of an item of the items in the cart and a fulfillment center of the item in the cart. The computer-implemented can further include generating embeddings for the clusters, and determining a cluster combination of cluster combinations with an optimal cost. The computer-implemented can additionally include re-ranking recommended items of the cluster combination with the optimal cost, and transmitting for displaying, on a device of a user, at least a subset of the recommended items of the cluster combination with the optimal cost, as re-ranked. Other embodiments are described.

Abstract: A method can include receiving, from a first sensor, an ambient temperature indicative of an amount of external heat to which a first storage container is exposed. The method can also include determining, with a first machine learning model, a first set of pre-cooling parameters for the first storage container based in part on factors comprising the ambient temperature indicative of an amount of external heat to which a first storage container is exposed, time of day, and a scheduled loading time for the first storage container. The method can further include transmitting a first request to a first pre-cooling system to initiate a cooling process for the first storage container in accordance with the first set of pre-cooling parameters. The method can also include predicting maintenance of the first storage container using a second machine learning model. Other embodiments are described.

Abstract: Example implementations relate to providing advertising content. A transaction event associated with a user is detected. A timing parameter is determined based on transaction data associated with the transaction event and user profile information of a user. The timing parameter is indicative of an estimated time for the user to approach a fixed digital display device after the transaction event. Advertising content for the user is determined based on the user profile information. The advertising content is displayed on the fixed digital display based on the timing parameter.

Abstract: Example implementations relate to systems and methods for re-ranking products of a query. Example computer implemented methods may include receiving an intermediate recall set of products of a query and obtaining features of a product of the intermediate recall set of products of the query. The computer implemented method can further include performing dense cross interactions between the query and the features of the product of the intermediate recall set of products using a cross-encoder model to generate a class prediction. The computer-implemented method can additionally include generating a re-rank score for the product of the intermediate recall set of products of the query by performing a model inference based at least on the class prediction. The computer-implemented method can also include re-ranking the product of the intermediate recall set of products based on the re-rank score for the product. Other embodiments are described.

Abstract: Example implementations relate to systems and methods for detecting disengagement. In an example, a system determines, by a risk identifier, predetermined risk labels based on the user data. The system determines, using a risk evaluator that receives input features, a risk of disengagement for a user. The system determines, using a risk interpreter that receives the input features and the predetermined risk labels, a disengagement reason for the user. The system also determines, based on the risk of disengagement and the disengagement reason, a disengagement prevention incentive for the user. The system further presents, at a computing device associated with the user, a user interface element for interacting with the disengagement prevention incentive.

Abstract: This application relates to apparatus and methods for automatically determining and providing digital customer insights based on historical customer data. In some examples, a computing device obtains user data for a user. In response, the computing device receives a plurality of product types relevant to the user and their corresponding relevance scores. For each product type, the computing device then receives a set of attributes, where each attribute is associated with an affinity score for the user. The computing device determines, for each product type, an overall score for each attribute and product type pair based on the relevance score for the product type and the affinity score for the corresponding attribute. At least one attribute and product type pair is presented to the user based on the corresponding overall score.

Abstract: A pallet return assembly includes at least one support member, a bracket member, a base member including a stopper member, and a lever that, when actuated, moves the base member and its stopper member from a pallet catch position to a pallet release position. In the pallet catch position, the stopper member catches a bottom of a pallet positioned on the roller tracks of the pallet bay and restricts the pallet from moving along the roller tracks. In the pallet release position, the stopper member no longer catches the bottom of the pallet positioned on the roller tracks and no longer restricts the pallet from moving along the roller tracks.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to wheel-based power generation on a cart for transporting commercial products. In some embodiments, a system may include at least one wheel that rotates in multiple directions; a first shaft coupled to the at least one wheel; a rotation transmitter coupled to the at least one wheel and the first shaft; a first gear coupled to the first shaft; a second gear coupled to the first gear; a second shaft coupled to the second gear; and a generator coupled to the second shaft to generate power by converting rotation of the at least one wheel into an alternating current power output. The system may include a control unit coupled to the generator to convert the alternating current power output into a direct current power, and a power storage component coupled to the generator, to store the direct current power output.

Abstract: A computer-implemented method including detecting respective one or more text boxes in each of multiple partial images of a text-bearing area. The method also can include determining respective one or more edge text boxes of the respective one or more text boxes in each of overlapping partial images of the multiple partial images, wherein each of the respective one or more edge text boxes comprise a respective incomplete text. The method additionally can include matching one or more pairs of corresponding edge text boxes from the respective one or more edge text boxes of two adjacent images of the overlapping partial images of the multiple partial images. The method also can include determining cross-image texts in the one or more pairs of the corresponding edge text boxes.

Abstract: Systems and methods of anomaly detection using a generalized time-series forecasting model are disclosed. A time-series dataset is received and a forecast is generated for the time-series dataset utilizing a trained generalized time-series forecasting model configured to utilize a fixed set of characteristic features. A first anomaly determination for the time-series dataset is generated based on a comparison of the forecast for the time-series dataset to the time-series dataset. In response to the first anomaly determination identifying an anomaly, an anomaly identification notification is transmitted to an additional system associated with the anomaly identification.

Abstract: Examples relate to a computer-implemented method of system including a processor that can perform certain operations. The operations can include obtaining campaign inputs for a campaign associated with product specifications for an advertiser. The operations also can include generating, using an approximate nearest neighbor similarity search, targeting cuts for a targeting tactic based at least on the campaign inputs. The targeting cuts can be personalized to the advertiser and the product specifications. The operations additionally can include generating an optimized ad group plan including one or more groups of the targeting cuts and, for each of the one or more groups of the targeting cuts, a respective recommended maximum bid, a respective expected amount of winning impressions, and a respective budget allocation. The operations further can include outputting the optimized ad group plan for the campaign. Other embodiments are described.