Titlebook: Progress in Image Analysis and Processing, ICIAP 2013; Naples, Italy, Septe Alfredo Petrosino Conference proceedings 2013 Springer-Verlag G

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Age Estimation Using Local Binary Pattern Kernel Density Estimate,n, we make use of the . support vector regression technique. The main contributions of our work include (i) evaluation of a pose correction method based on simple image flipping and (ii) a comparison of two local binary pattern based facial representations, namely a spatially enhanced histogram and

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地殼

A Fast Jensen-Shannon Subgraph Kernel,dges, the worst-case time complexity for our kernel is .(. .?+?.), in contrast to .(. .) for the classic graph kernel. Key to this efficiency is that we manage to compute the Jensen-Shannon divergence involved in our kernel with .(. .) operations. This computational strategy enables our subgraph ker

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finale

978-3-642-41180-9Springer-Verlag GmbH Germany, part of Springer Nature 2013

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Progress in Image Analysis and Processing, ICIAP 2013978-3-642-41181-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

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