The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 24, 2024

Filed:

Mar. 26, 2020
Applicant:

Sita Information Networking Computing Uk Limited, Middlesex, GB;

Inventor:

Adrian Sisum Liu, Middlesex, GB;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/00 (2022.01); G06N 7/01 (2023.01); G06N 20/20 (2019.01); G06V 10/56 (2022.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01);
U.S. Cl.
CPC ...
G06V 20/10 (2022.01); G06N 7/01 (2023.01); G06N 20/20 (2019.01); G06V 10/56 (2022.01); G06V 10/762 (2022.01); G06V 10/763 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/809 (2022.01); G06V 10/82 (2022.01);
Abstract

An item classification system for use in an item handling system is disclosed. The classification system comprises processing means configured to: process an image of an item to determine, based on a first model (), one or more predetermined first item types, each first item type defined by one or more first item characteristics; process the image to determine, based on the first model (), a first probability associated with each first item type wherein each first probability is indicative of the likelihood that the item has the first characteristics defining each determined first item type; process the image to determine, based on a second model (), one or more predetermined second item types, each second item type defined by one or more second item characteristics; process the image to determine, based on the second model (), a second probability associated with each second item type wherein each second probability is indicative of the likelihood that the item has the second characteristics defining each second item type; and classify the item according to each first item type and each second item type and the probability associated with each first item type and the probability associated with each second item type.


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