dc.contributor.authorZhao, Wei
dc.contributor.authorWang, Han
dc.contributor.authorHuang, Guang-Bin
dc.date.accessioned2015-12-16T08:43:03Z
dc.date.available2015-12-16T08:43:03Z
dc.date.issued2015
dc.identifier.citationZhao, W., Wang, H., & Huang, G.-B. (2015). Multifeature Extreme Ordinal Ranking Machine for Facial Age Estimation. Mathematical Problems in Engineering, 2015, 840840-.en_US
dc.identifier.issn1024-123Xen_US
dc.identifier.urihttp://hdl.handle.net/10220/39103
dc.description.abstractRecently the state-of-the-art facial age estimation methods are almost originated from solving complicated mathematical optimization problems and thus consume huge quantities of time in the training process. To refrain from such algorithm complexity while maintaining a high estimation accuracy, we propose a multifeature extreme ordinal ranking machine (MFEORM) for facial age estimation. Experimental results clearly demonstrate that the proposed approach can sharply reduce the runtime (even up to nearly one hundred times faster) while achieving comparable or better estimation performances than the state-of-the-art approaches. The inner properties of MFEORM are further explored with more advantages.en_US
dc.format.extent9 p.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesMathematical Problems in Engineeringen_US
dc.rights© 2015 Wei Zhao 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.en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleMultifeature Extreme Ordinal Ranking Machine for Facial Age Estimationen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1155/2015/840840
dc.description.versionPublished versionen_US


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