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• W2032875197 abstract "Online signature verification methods examine the dynamics of the handwriting process to decide whether a signature is probably genuine or forged. Most of the previously proposed methods for online signature verification apply Neural Networks, Dynamic Time Warping, or Hidden Markov Model for classification and they consider several aspects, like planar coordinates, pressure, velocity, and acceleration with respect to time. Here we apply a non-parametric statistical test for a comparison of features and the verification of signatures." @default.
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• W2032875197 date "2014-09-01" @default.
• W2032875197 modified "2023-10-16" @default.
• W2032875197 title "Online Signature Verification Based on Kolmogorov-Smirnov Distribution Distance" @default.
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• W2032875197 doi "https://doi.org/10.1109/icfhr.2014.129" @default.
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