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We propose a novel, language-neutral approach for searching online handwritten text using Frechet distance. Online handwritten data, which is available as a time series (x,y,t), is treated as representing a parameterized curve in two-dimensions and the problem of searching online handwritten text is posed as a problem of matching two curves in a two-dimensional Euclidean space. Frechet distance is...
In this paper we propose a novel family of kernels for multivariate time-series classification problems. Each time-series is approximated by a linear combination of piecewise polynomial functions in a reproducing kernel Hilbert space by a novel kernel interpolation technique. Using the associated kernel function a large margin classification formulation is proposed which can discriminate between two...
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