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Mathematical Problems in Engineering - Volume 2014 2014, Article ID 242846, 8 pages -

Research ArticleSchool of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China

Received 3 September 2013; Revised 19 February 2014; Accepted 6 March 2014; Published 6 April 2014

Academic Editor: Yang Tang

Copyright © 2014 Yuyu Liang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Age estimation is a complex issue of multiclassification or regression. To address the problems of uneven distribution of age database and ignorance of ordinal information, this paper shows a hierarchic age estimation system, comprising age group and specific age estimation. In our system, two novel classifiers, sequence k-nearest neighbor SKNN and ranking-KNN, are introduced to predict age group and value, respectively. Notably, ranking-KNN utilizes the ordinal information between samples in estimation process rather than regards samples as separate individuals. Tested on FG-NET database, our system achieves 4.97 evaluated by MAE mean absolute error for age estimation.





Autor: Yuyu Liang, Xianmei Wang, Li Zhang, and Zhiliang Wang

Fuente: https://www.hindawi.com/



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