CNN-based learning method, learning device for selecting useful training data and test method, test device using the same
US10504027B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 26, 2018 |
| Grant date | Dec 10, 2019 |
| Priority date | — |
| Expiry date | Oct 26, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A convolutional neural network (CNN)-based learning method for selecting useful training data is provided. The CNN-based learning method includes steps of: a learning device (a) instructing a first CNN module (i) to generate a first feature map, and instructing a second CNN module to generate a second feature map; (ii) to generate a first output indicating identification information or location information of an object by using the first feature map, and calculate a first loss by referring to the first output and its corresponding GT; (b) instructing the second CNN module (i) to change a size of the first feature map and integrate the first feature map with the second feature map, to generate a third feature map; (ii) to generate a fourth feature map and to calculate a second loss; and (c) backpropagating the auto-screener's loss generated by referring to the first loss and the second loss.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.