Clustering historical images using a convolutional neural net and labeled data bootstrapping
US10318846B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 28, 2016 |
| Grant date | Jun 11, 2019 |
| Priority date | — |
| Expiry date | Apr 18, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/7788
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for classifying historical images. A feature extractor may create feature vectors corresponding to a plurality of images. A first classification of the plurality of images may be performed based on the plurality of feature vectors, which may include assigning a label to each of the plurality of images and assigning a probability for each of the assigned labels. The assigned probability for each of the assigned labels may be related to a statistical confidence that a particular assigned label is correctly assigned to a particular image. A subset of the plurality of images may be displayed to a display device. An input corresponding to replacement of an incorrect label with a corrected label for a certain image may be received from a user. A second classification of the plurality of images based on the input from the user may be performed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.