Method for auto-labeling training images for use in deep learning network to analyze images with high precision, and auto-labeling device using the same
US10540572B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 31, 2019 |
| Grant date | Jan 21, 2020 |
| Priority date | — |
| Expiry date | Jan 31, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/56
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for auto-labeling a training image to be used for learning a neural network is provided for achieving high precision. The method includes steps of: an auto-labeling device (a) instructing a meta ROI detection network to generate a feature map and to acquire n current meta ROIs, on the specific training image, grouped according to each of locations of each of the objects; and (b) generating n manipulated images by cropping regions, corresponding to the n current meta ROIs, on the specific training image, instructing an object detection network to output each of n labeled manipulated images having each of bounding boxes for each of the n manipulated images, and generating a labeled specific training image by merging the n labeled manipulated images. The method can be performed by using an online learning, a continual learning, a hyperparameter learning, and a reinforcement learning with policy gradient algorithms.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.