Method of automatically training a classifier hierarchy by dynamic grouping the training samples
US8948500B2 · kind B2 · utility
4Cited by
1References
17Claims
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Key dates
| Filing date | May 31, 2012 |
| Grant date | Feb 3, 2015 |
| Priority date | — |
| Expiry date | Jul 4, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/06
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention uses dynamic grouping to divide up training samples to train different classification nodes. At the beginning of the training, all samples are in the same group. A clustering process is applied in the feature space of the selected feature vectors with cluster indexes accumulated. The average of all the accumulated cluster indexes is used as the threshold for splitting the samples into two groups. When the splitting criterion is met, samples are split into two groups based on their similarity in the feature space.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.