Patent ID: 11907841
Assignee: nan
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 18:
19. A non-transitory computer-readable medium having stored thereon computer executable instructions that when executed by a computer, causes the computer to execute operations, the operations comprising:
receiving an image set associated with each of a plurality of known consumer products, the image set being created by a camera system and received by a neural network from the camera system;
storing the image set as a template image set in a database connected to the neural network:
generating identification tags associated with characteristics of each of the known consumer products, the identification tags being generated by the neural network;
assigning a set of identification tags to the template image set of each of the known consumer products, the set of identification tags being assigned by the neural network;
generating by the neural network a machine learning model which is trained based on the assigned set of identification tags to output one consumer product from the plurality of known consumer products;
receiving an input image of an unknown consumer product, the input image being received by a recognition application;
comparing by the recognition application the input image of the unknown consumer product to the template image sets of the known consumer products;
determining by the recognition application whether the input image of the unknown consumer product matches the template image set of one of the known consumer products, wherein determining whether the input image of the unknown consumer product matches the template image set of the known consumer product comprises one of the steps of:
determining that an exact match exists between the input image of the unknown consumer product and the template image set of one of the plurality of known consumer products;
determining that a close match exists between the input image of the unknown consumer product and the template image set of one of the plurality of known consumer products; and
determining that no match exists between the input image of the unknown consumer product and the template image set of one of the plurality of known consumer products;

identifying the unknown consumer product when the image of the unknown consumer product matches the template image set of one of the plurality of known consumer products; the unknown consumer product being identified by the recognition application;
receiving feedback from a system user regarding accuracy of identification of the unknown consumer product, the feedback being received by a training module; and
adjusting settings in at least one of the camera system, the neural network, and the recognition application based on the feedback received by the training module from the system user.