Imaging system with unsupervised learning
AssigneeRehrig Pacific Company
InventorsJustin Michael Brown, Daniel James Thyer
Life of this patent
Estimating the term…
Abstract
An imaging system and method uses grouping and elimination to label images of unknown items. The items may be stacked together with known or unknown items. The items may be packages, such as packages of beverage containers. A machine learning model may be used to infer skus of the packages. The machine learning model is trained on known skus but is not trained on unknown skus. Multiple images of the same unknown sku are grouped using the machine learning model. Elimination based upon lists of expected skus is used to label each group of unknown skus.
Claims14
A method for identifying a plurality of items in a stack using a computing system including at least one machine learning model, the method including:
- a) receiving at least one image of the plurality of items in the stack;
- b) analyzing the at least one image using the at least one machine learning model;
- c) comparing the plurality of items to a list of expected items;
- d) repeating steps a) to c) for each of a plurality of stacks of the plurality of items;
- e) using the at least one machine learning model, forming a plurality of groups of images of the plurality of items in the plurality of stacks;
- and
- f) based upon the expected lists of items, assigning one of the expected items to each of the plurality of groups of images.
A computing system for evaluating a stack of a plurality of items comprising:
- at least one processor;
- and
- at least one non-transitory computer-readable medium storing:
- at least one machine learning model;
- and
- instructions that, when executed by the at least one processor, cause the computing system to perform operations comprising:
- a) receiving at least one image of the stack of the plurality of items;
- b) analyzing the at least one image using at least one machine learning model;
- c) comparing the plurality of items to a list of expected items;
- d) repeating steps a) to c) for each of a plurality of stacks of the plurality of items;
- e) using the at least one machine learning model, forming a plurality of groups of images of the plurality of items in of the stacks;
- and
- f) based upon the expected lists of items, assigning one of the expected items to each of the plurality of groups of images.
Dependencies are inferred from the claim text.