Abstract: A method is provided for training at least one classifier model used by an artificial intelligence (AI) system to recognize each of a set of objects and to assign each of the set of objects to a class.

Abstract: A method is provided for assigning a classification to consumer packaged goods (CPGs). The method includes capturing an image of a plurality of CPGs arranged on a shelf; providing the captured image to a CPG detector; identifying all of the CPGs in the image; producing a set of cropped images, wherein each cropped image shows a single CPG as it appears in the image; and for each member of the set of cropped images, assigning a classification to the CPG in the member of the set of cropped images and establishing a confidence for the assigned classification through a process that includes the steps of (a) identifying a first set of reference images of CPGs whose classification is known, wherein each member of the first set of reference images is semantically similar to the member of the set of cropped images, and (b) identifying details in the member of the set of cropped images that differentiates it from a second set of reference images of CPGs whose classification is known.

Abstract: A method is provided for identifying consumer packaged goods (CPGs). The method includes providing to a machine learning classifier a set of images containing at least one CPG; receiving from the machine learning classifier an indication that the machine learning classifier cannot reliably identify a designated CPG in the set of images; determining whether the designated CPG is a product in a product catalog; if the designated CPG is in the product catalog, then associating the designated CPG with a Global Trade Item Number (GTIN); and if the designated product is not in the product catalog, then designating the CPG as a potentially new product. Notably, this approach allows partially identified products to be treated as full-fledged members of the product catalog, thus allowing data to be collected on these products even before they have been fully identified and their GTINs have been resolved.

Abstract: A system for managing consumer packaged goods (CPGs) is disclosed. The system includes a front end and a back end. The front end includes a mobile, airborne platform equipped with a digital image capturing device, and a wireless communications device. The backend is in communication with the front end via the wireless communications device, and includes a combinational convolutional neural network which derives models based on input data, a convolutional neural network which generates perception scoring utilizing input put from said combinational convolutional neural network, and a recurrent neural network which makes behavior predictions based on input from said convolutional neural network. The front end captures images of CPGs on a shelf, wherein the CPGs are subject to depletion over time, and wherein the backend generates predictions regarding the depletion state of the CPGs on the shelf as a function of time.

Abstract: A system is provided for identifying consumer packaged goods (CPGs).

Abstract: A system is provided for identifying consumer packaged goods (CPGs).