Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4943193 | Expert Systems with Applications | 2017 | 50 Pages |
Abstract
Experiments are conducted on five public databases (MORPH II, PAL, IoG, LFW and FERET) and another two challenge databases (Apparent age; Smile and Gender) of the 2016 ChaLearn Looking at People and Faces of the World Challenge and Workshop. These experiments show stable and good results. We present many comparisons against state-of-the-art methods. We also provide a study about cross-database evaluation. We quantitatively measure the performance drop in age estimation and in gender classification when the ethnicity attribute is misclassified.
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Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
SE. Bekhouche, A. Ouafi, F. Dornaika, A. Taleb-Ahmed, A. Hadid,