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Volume: 29 | Article ID: art00017
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Evaluating Age Estimation Using Deep Convolutional Neural Nets
  DOI :  10.2352/ISSN.2470-1173.2017.17.COIMG-432  Published OnlineJanuary 2017
Abstract

Age estimation from a facial image is still a challenge due to the variations caused by different aging processes, face appearance, human expression, and face pose. In this paper, we provide a comparative study for age estimation using classic image features as well as deep image features that are provided by pre-trained deep Convolutional Neural Networks. The presented work compares several image features. The experiments are conducted on two face datasets: MORPH II and PAL. In the light of the conducted experiments, image features that are providing the best performances can be highlighted.

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C. Belver, I. Arganda-Carreras, F. Dornaika, "Evaluating Age Estimation Using Deep Convolutional Neural Netsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Computational Imaging XV,  2017,  pp 100 - 105,  https://doi.org/10.2352/ISSN.2470-1173.2017.17.COIMG-432

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