Active learning-based data labeling service using an augmented manifest
US11443232B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 29, 2019 |
| Grant date | Sep 13, 2022 |
| Priority date | — |
| Expiry date | May 20, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for active learning-based data labeling are described. An active learning-based data labeling service enables a user to build and manage large, high accuracy datasets for use in various machine learning systems. Machine learning may be used to automate annotation and management of the datasets, increasing efficiency of labeling tasks and reducing the time required to perform labeling. Embodiments utilize active learning techniques to reduce the amount of a dataset that requires manual labeling. As subsets of the dataset are labeled, this label data is used to train a model which can then identify additional objects in the dataset without manual intervention. The label data can be added to an augmented manifest, the augmented manifest can be used to filter the dataset to perform further labeling jobs on the same or different subsets of the dataset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.