Learning method and testing method for object detector based on R-CNN, and learning device and testing device using the same
US10304009B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 8, 2018 |
| Grant date | May 28, 2019 |
| Priority date | — |
| Expiry date | Oct 8, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20081
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for learning an object detector based on an R-CNN by using a first to an n-th filter blocks respectively generating a first to an n-th feature maps through convolution operations in sequence, and a k-th to a first upsampling blocks respectively coupled with the first to the n-th filter blocks is provided. The method includes steps of: a learning device instructing the k-th upsampling block to the first upsampling block to generate a (k−1)-st pyramidic feature map to the first pyramidic feature map respectively; instructing an RPN to generate each ROI corresponding to each candidate region, and instructing a pooling layer to generate a feature vector; and learning parameters of the FC layer, the k-th to the first upsampling blocks, and the first to the n-th filter blocks by backpropagating a first loss generated by referring to object class information, object regression information, and their corresponding GTs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.