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• W2066808422 startingPage "785" @default.
• W2066808422 abstract "This paper presents a cost-sensitive ordinal hyperplanes ranking algorithm for human age estimation based on face images. The proposed approach exploits relative-order information among the age labels for rank prediction. In our approach, the age rank is obtained by aggregating a series of binary classification results, where cost sensitivities among the labels are introduced to improve the aggregating performance. In addition, we give a theoretical analysis on designing the cost of individual binary classifier so that the misranking cost can be bounded by the total misclassification costs. An efficient descriptor, scattering transform, which scatters the Gabor coefficients and pooled with Gaussian smoothing in multiple layers, is evaluated for facial feature extraction. We show that this descriptor is a generalization of conventional bioinspired features and is more effective for face-based age inference. Experimental results demonstrate that our method outperforms the state-of-the-art age estimation approaches." @default.
• W2066808422 created "2016-06-24" @default.
• W2066808422 creator A5063860136 @default.
• W2066808422 creator A5072890368 @default.
• W2066808422 date "2015-03-01" @default.
• W2066808422 modified "2023-09-25" @default.
• W2066808422 title "A Learning Framework for Age Rank Estimation Based on Face Images With Scattering Transform" @default.
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• W2066808422 doi "https://doi.org/10.1109/tip.2014.2387379" @default.
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• W2066808422 hasPublicationYear "2015" @default.
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