US 2023/0274641 A1 · HIERARCHICAL TRANSFER LEARNING SYSTEM

Abstract

Systems, methods, and other embodiments described herein relate to improving the performance of a device in different geographic locations by using transfer learning to provide a customized learning model for the different locations. In one embodiment, a method includes receiving segments of a model from separate members in a geographic hierarchy and assembling the segments into the model. The segments include at least a first segment, a second segment, and a third segment. The method includes processing sensor data using the model to provide an output for assisting a device.

Claims20

Dependent claims

A system, comprising:

one or more processors, and
a memory communicably coupled to the one or more processors and storing:
a control module including instructions that, when executed by the one or more processors cause the one or more processors to:
receive segments of a model from separate members in a geographic hierarchy;
assemble the segments into the model, wherein the segments include at least a first segment, a second segment, and a third segment;
and
process sensor data using the model to provide an output for assisting a device.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application

17/681,092Filed 25 Feb 2022

Published

31 Aug 2023

Term ends

Not estimatedThe source records don’t support an estimate.

Classification12 codes

G08G 1/096775
Where the system is characterised by the origin of the information transmission: where the origin of the information is a central station
G06N 3/096
Learning methods: transfer learning
G06V 10/82
Using pattern recognition or machine learning: using neural networks
G06V 10/87
Using pattern recognition or machine learning: using selection of the recognition techniques, e.g. of a classifier in a multiple classifier system

Hierarchical transfer learning system

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Hierarchical transfer learning system

Life of this patent

Abstract

Claims20