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US Patent 11887046 Updating machine learning systems using previous output data

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Contents

Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
118870460
Patent Inventor Names
Félix Joseph Étienne Pageau0
David Echevarria Ignacio0
Aaron Craig Thompson0
Gary Paolo Raden0
Sridhar Boyapati0
David William Bettis0
Sudarshan Narasimha Raghavan0
Christopher Andrew Stephens0
...
Date of Patent
January 30, 2024
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Patent Application Number
169452890
Date Filed
July 31, 2020
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Patent Citations
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US Patent 8009864 Determination of inventory conditions based on image processing
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US Patent 7225980 Shopping cart with RFID capability
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US Patent 7290707 Tele-inventory system, and in-shop terminal and remote management apparatus for the system
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US Patent 7769221 System and method for visual verification of item processing
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US Patent 7949568 Determination of product display parameters based on image processing
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US Patent 8189855 Planogram extraction based on image processing
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US Patent 8321302 Inventory management system
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US Patent 8630924 Detection of stock out conditions based on image processing
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...
Patent Primary Examiner
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Asfand M Sheikh
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CPC Code
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G06Q 10/08
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H04N 7/181
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G06V 40/10
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G06T 7/0004
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G06Q 10/087
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Patent abstract

A system may use sensor data from a facility to generate tentative values associated with an event, such as the identification of an item removed from a shelf of the facility. A confidence value associated with each of the tentative values may be less than a confidence threshold. In response, inquiry data seeking confirmation of a tentative value from an associate is generated and sent to one or more associates in the facility. Responses from the associates are collected to determine a selection of one of the tentative values. The selected tentative value is designated as output data for the system. Thereafter, the output data and the original sensor data are designated as training data, which can then be used to train or update machine learning systems. Subsequent use of the updated machine learning systems can yield more accurate results.

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