| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 536665 | Pattern Recognition Letters | 2008 | 10 Pages |
Abstract
A novel framework that applies Bayes-based confidence measure for multiple classifier system fusion is proposed. Compared with ordinary Bayesian fusion, the presented approach can lead to reductions as high as 37% and 35% in EER and ROC curve area, respectively, in speaker verification.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Fernando Huenupán, Nestor Becerra Yoma, Carlos Molina, Claudio Garretón,