Abstract: Example methods, apparatus, and articles of manufacture to classify labels based on images using artificial intelligence are disclosed. An example apparatus includes a regional proposal network to determine a first bounding box for a first region of interest in a first input image of a product; and determine a second bounding box for a second region of interest in a second input image of the product; a neural network to: generate a first classification for a first label in the first input image using the first bounding box; and generate a second classification for a second label in the second input image using the second bounding box; a comparator to determine that the first input image and the second input image correspond to a same product; and a report generator to link the first classification and the second classification to the product.

Abstract: Methods, systems, articles of manufacture, and apparatus to recalibrate confidences for image classification are disclosed. An example apparatus to classify an image includes an image crop detector to detect a first image crop from the image, the first image crop corresponding to a first object, a grouping controller to select a second image crop corresponding to a second object at a location of the first object, a prediction generator to, in response to executing a trained model, determine a label corresponding to the first object and a confidence level associated with the label, and a confidence recalibrator to recalibrate the confidence level based on a probability of the first object having a first attribute based on the second object having a second attribute, the confidence level recalibrated to increase an accuracy of the image classification.

Abstract: An example system disclosed herein includes an analyzer to analyze first neuro-response data and second neuro-response data and a selector to identify a candidate location in source material for introduction of an advertisement or entertainment based on first neuro-response data and second neuro-response data. The analyzer is to detect a first pattern of oscillation in a first frequency band of third neuro-response data; detect a second pattern of oscillation in a second frequency band of the third neuro-response data; determine a degree of phase synchrony or amplitude synchrony based on the first pattern of oscillation and the second pattern of oscillation; and determine an effectiveness of the advertisement or entertainment based on the degree of phase synchrony or amplitude synchrony.

Abstract: An example system disclosed herein for transforming neuro-response data into media ratings includes a data collector to obtain first neuro-response from a first subject exposed to a first media and second neuro-response data from a second subject exposed to a second media. The first media broadcast is before a time of the second media. The example system includes an analyzer to integrate the first neuro-response data with ratings data for the first media to generate a first rating for the first media. The ratings data is based on set-top box data associated with a media presentation device presenting the first media. The analyzer is to transform the second neuro-response data into a second rating for the second media based on the first rating.

Abstract: Methods and apparatus to search datasets are disclosed. An example disclosed method includes receiving a search request having at least two criteria and assigning the criteria to a first group according to a logical relationship between the criteria. The example method further includes determining which of the criteria in the first group is satisfied by a least amount of records in a database based on a plurality of counts, the counts respectively indicative of a number of corresponding records in the database satisfying a respective one of criteria exhibited by the database, and identifying a reduced set of records in the database to be searched, the reduced set of records corresponding to the first or second criteria that is satisfied by the least amount of records in the database, and reducing a search time associated with the search request by searching the reduced set of records from the database.

Abstract: Methods, apparatus, systems and articles of manufacture methods, systems, apparatus and articles of manufacture to model ecommerce sales are disclosed. A system to model to eCommerce sales includes a trend identifier to compute commerce metric differences corresponding to products, the commerce metric differences based on first commerce metrics scraped at a first time and second commerce metrics scraped at a second time, a splitter to split the commerce metric differences into a first portion of the commerce metric differences corresponding to a first dataset of eCommerce cooperators, and into a second portion of the commerce metric differences corresponding to a second dataset of eCommerce non-cooperators, a machine learning engine to infer sales data by estimating eCommerce non-cooperators sales based on the second portion of the commerce metric differences, and a sales allocator to estimate sales missing from collected sales data based on the estimate eCommerce non-cooperators sales.

Abstract: An ingredient data system that ingests text and graphics of product labels associated with consumer products to check compliance with rules pertaining to what can be included on the product labels generally includes a memory having instructions stored thereon, and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the base attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products designated under one or more of the base attributes associated with the first request, and at least a portion of details of noncompliance when one or more of the pieces of the constituent information are identified as impermissible according to the compliance information.

Abstract: Examples methods, apparatus/systems and articles of manufacture for auditing point-of-sale images are disclosed herein. Example methods disclosed herein include comparing a region of interest of an image displayed via a user interface with a plurality of reference product images stored in a database to identify a plurality of candidate product images from the plurality of reference product images as potential matches to a first product depicted in the image. For example, the candidate product images are associated with respective confidence levels indicating respective likelihoods of matching the first product. Disclosed example methods also include displaying, via the user interface, the candidate product images simultaneously with the image in a manner based on the respective confidence levels, and automatically selecting a first one of the candidate product images as matching the first product based on the respective confidence levels.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor auditing devices. An example apparatus includes a workload analyzer to obtain alert data related to a potential new product from an auditing device, and a product analyzer to identify a product within the alert data to determine if the product has been previously identified by another auditing device. In response to determining that the product has not been previously identified, the example apparatus includes an alert analyzer to cluster the alert data based on characteristics associated with an auditor profile of the auditing device, and determine a probability of transmitting the alert data to other auditing devices based on the clustered alert data. The example apparatus also includes an alert authorizer to suppress the alert data from being transmitted to the other auditing devices to reduce an amount of network resources required for subsequent processing when the probability does not satisfy a threshold.

Abstract: Methods and apparatus to identify retail pricing strategies are disclosed herein. An example apparatus for identifying a pricing strategy employed by a store includes a calculator to calculate a first pricing strategy variable for the store based on sales data of the store. The example apparatus includes an index creator to index the first pricing strategy variable against aggregated data for a plurality of stores to generate a pricing index. The example apparatus includes a pricing strategy identifier to identify a pricing strategy for the store based on the pricing index.

Abstract: Example headsets and methods for gathering electroencephalographic signals are disclosed herein. An example headset disclosed herein includes a cap to be worn on a head of a person and a first electrode carried by the cap. The first electrode holder defines a first opening therethrough. The example headset includes a first electrode that insertable into the first opening. The first electrode has a first length and is adjustable in the first opening to a first plurality of discrete positions having different depths of insertion relative to the first opening. The first electrode is to engage the head of the person when inserted a sufficient depth into the first opening. The example headset also includes a second electrode that is interchangeable with the first electrode and insertable into the first opening.

Abstract: Methods, systems, articles of manufacture, and apparatus to monitor the availability of products for purchase are disclosed. An apparatus includes a communications interface to receive market data from data collectors, the market data including stock status data indicative of different stock statuses for a product in different retail establishments. The apparatus further includes a reward profile analyzer reduce error in collection of the stock status data by: generating a reward profile for the market data, the reward profile to define different reward levels for different types of the stock statuses indicated by the stock status data; determining a distribution of rewards among the different data collectors based on the reward profile and different portions of the market data provided by corresponding ones of the different data collectors; and providing the rewards to the different data collectors based on the distribution.

Abstract: Methods, apparatus, systems and articles of manufacture to adjust content presented to an individual are disclosed. An example system includes a first modality sensor to measure a first response of an individual to first content during a first time frame and a second modality sensor to measure a second response of the individual to the first content during the first time frame. The first modality sensor is to measure a third response of the individual to first content during a second time frame, and the second modality sensor is to measure a fourth response of the individual to the first content during the second time frame. The example system also includes a mental classifier executing instructions to determine a first mental classification of the individual based on a first comparison of the first response to a first threshold and a second comparison of the second response to a second threshold.

Abstract: An example system includes a first headset including first sensor to gather first user data from a first subject during exposure to media, the first user data including at least one of psychophysiological data or physiological data; and a first processor to generate first data indicative of an emotional response of the first subject based on the first user data. The example system includes a second headset including a second sensor to gather second user data from the second subject during exposure to the media, the second user data including at least one of psychophysiological data or physiological data; a second processor to generate second data indicative of an emotional response of the second subject based on the second user data and synchronize the second data with the first data to generate synchronized response data; and a second transmitter to transmit the synchronized response data to a central processor.

Abstract: An example system includes an analyzer to identify a degree of amplitude synchrony between a first pattern in a first frequency band in first neuro-response data and a second pattern in a second frequency band in the first neuro-response data, the first neuro-response data gathered via a first modality of collection from a subject while the subject is exposed to media, and modify the degree of amplitude synchrony in response to activity in second neuro-response data, the second neuro-response data gathered via a second modality of collection from the subject while the subject is exposed to the media, the activity corresponding in time to at least a portion of the first pattern or the second pattern. The example system includes an estimator to determine an effectiveness of the media based on the modified degree of amplitude synchrony.

Abstract: An example system includes an analyzer to identify first activity in first neuro-response data, the first activity generated in response to exposure of a subject to a first stimulus prior to exposure to an advertisement or entertainment; identify second activity in second neuro-response data, the second activity generated in response to re-exposure of the subject to the first stimulus after to exposure to the advertisement or entertainment; calculate a differential event related potential measurement; and calculate a differential event related power spectral perturbation. The example system includes a resonance estimator to determine a subject resonance measurement to the advertisement or the entertainment based on the differential event related potential measurement and adjust at least one of the subject resonance measurement or the differential event related potential measurement based on the differential event related power spectral perturbation to generate an adjusted subject resonance measurement.

Abstract: Methods and apparatus are disclosed to forecast new product launch sourcing. An example method includes identifying shared attributes between the new product and a plurality of existing products in the target market, calculating theoretical co-penetration values between the attributes shared between the new product and at least one of the plurality of existing products, calculating actual co-penetration values between the attributes shared between the new product and at least one of the plurality of existing products, calculating an attribute distance value between corresponding ones of the theoretical and actual co-penetration values, and calculating a percent volume of the new product expected to be sourced from one of the plurality of existing products based on the attribute distance value.

Abstract: The present disclosure relates to biologically and behaviorally based methods of measuring audience response to a short stimulus.

Abstract: A method comprises displaying visual representations of a plurality of product alternatives each including at least one attribute variant to a respondent, receiving from the respondent an indication of a preferred one of the plurality of product alternatives, transmitting a request to the respondent to identify at least one attribute variant of a non-preferred product alternative that is preferred by the respondent to the corresponding attribute variant of the preferred one of the plurality of product alternatives and receiving a response from the respondent identifying at least one attribute variant of a non-preferred product alternative that is preferred by the respondent to the corresponding attribute variant of the preferred one of the plurality of product alternatives.