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• W3106838313 endingPage "110611" @default.
• W3106838313 startingPage "110611" @default.
• W3106838313 abstract "Dynamic signatures are recordings of signatures made on digitizing devices such as tablet PCs. These handwritten signatures contain both dynamic and spatial information on every data point collected during the signature movement and can therefore be described in the form of multivariate data. The management of dynamic signatures represents a challenge for the forensic science community through its novelty and the volume of data available. Much as for static signatures, the authenticity of dynamic signatures may be doubted, which leads to a forensic examination of the unknown source signature. The Bayes’ factor, as measure of evidential support, can be assigned with statistical models to discriminate between competing propositions. In this respect, the limitations of existing probabilistic solutions to deal with dynamic signature evidence is pointed out and explained in detail. In particular, the necessity to remove the independence assumption between questioned and reference material is emphasized." @default.
• W3106838313 created "2020-12-07" @default.
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• W3106838313 date "2021-01-01" @default.
• W3106838313 modified "2023-10-05" @default.
• W3106838313 title "Bayesian multivariate models for case assessment in dynamic signature cases" @default.
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• W3106838313 doi "https://doi.org/10.1016/j.forsciint.2020.110611" @default.
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