US 2026/0087476 A1 · Devices and Methods Utilizing Machine Learning for Item Identification

Abstract

Methods and devices utilizing machine learning for item identification are disclosed herein. The method captures an image of an item present in a region. The method classifies, based on the image, the item utilizing a machine learning model, and generates, utilizing the machine learning model, one or more candidate items and a score for each candidate item based on the classified item. The method determines whether a score of a candidate item among the one or more candidate items exceeds a threshold. If a score of a candidate item among the one or more candidate items does not exceed the threshold, the method retrieves data associated with each candidate item. The method modifies a score of each candidate item based on the retrieved data and selects a candidate item having a highest modified score. The method updates the database based on the selected candidate item and displays the selected candidate item.

Claims23

Dependent claims

A method, comprising:

capturing, via an imager of a device, an image of an item present within a region, the imager having a field of view (FOV) extending at least partially over the region;
classifying, based on the image, the item utilizing a machine learning model;
generating, utilizing the machine learning model, one or more candidate items and a score for each candidate item based on the classified item;
determining whether a score of a candidate item among the one or more candidate items exceeds a threshold;
responsive to determining the score of a candidate item among the one or more candidate items does not exceed the threshold, retrieving, from a database, data associated with each candidate item;
modifying a score of each candidate item based on the retrieved data associated with each candidate item;
selecting a candidate item having a highest modified score;
updating the database based on the selected candidate item having the highest modified score;
and
displaying the selected candidate item having the highest modified score.

7 more elements

A device, comprising:

an imager having a field of view (FOV) extending at least partially over a region;
one or more memories;
and
one or more processors, communicatively coupled to the one or more memories, configured to:
capture, via the imager, an image of an item present within the region;
classify, based on the image, the item utilizing a machine learning model;
generate, utilizing the machine learning model, one or more candidate items and a score for each candidate item based on the classified item;
determine whether a score of a candidate item among the one or more candidate items exceeds a threshold;
responsive to determining the score of a candidate item among the one or more candidate items does not exceed the threshold, retrieve, from a database, data associated with each candidate item;
modify a score of each candidate item based on the retrieved data associated with each candidate item;
select a candidate item having a highest modified score;
update the database based on the selected candidate item having the highest modified score;
and
display the selected candidate item having the highest modified score.

11 more elements

A non-transitory computer-readable medium storing instructions thereon that, when executed by one or more processors, cause the one or more processors to:

capture, via an imager of a device, an image of an item present within a region, the imager having a field of view (FOV) extending at least partially over the region;
classify, based on the image, the item utilizing a machine learning model;
generate, utilizing the machine learning model, one or more candidate items and a score for each candidate item based on the classified item;
determine whether a score of a candidate item among the one or more candidate items exceeds a threshold;
responsive to determining the score of a candidate item among the one or more candidate items does not exceed the threshold, retrieve, from a database, data associated with each candidate item;
modify a score of each candidate item based on the retrieved data associated with each candidate item;
select a candidate item having a highest modified score;
update the database based on the selected candidate item having the highest modified score;
and
display the selected candidate item having the highest modified score.

7 more elements

Dependencies are inferred from the claim text.

Devices and Methods Utilizing Machine Learning for Item Identification

Life of this patent

Devices and Methods Utilizing Machine Learning for Item Identification

Life of this patent

Abstract

Claims23