Vehicle resiliency, driving feedback and risk assessment using machine learning-based vehicle wear scoring
US12124930B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | May 22, 2023 |
| Grant date | Oct 22, 2024 |
| Priority date | — |
| Expiry date | May 22, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG07C5/008
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning model is manufactured by a process including retrieving training data, minimizing a loss function, wherein the training data may include labeled or unlabeled data, the machine learning model generating a prediction. A machine learning training/operation server includes a processor and a memory storing instructions that, when executed by the processor, cause the server to retrieve training data, input a training input, analyze the training input to generate a prediction, generate a loss score, and store the trained machine learning model. A method for training a machine learning model includes receiving training data, inputting a training input, analyzing the training input, generating a loss score, and storing the trained machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.