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Titlebook: Computational Forensics; Third International Zeno J. M. H. Geradts,Katrin Y. Franke,Cor J. Veen Conference proceedings 2009 Springer-Verla

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Application to Optimal Stopping,arating line between the clusters in feature space. Deconvolution image processing parameters are determined from the separating line. A number of examples of applications in forensic casework are presented.
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Random elements in linear spaces,dence given the estimated within-source and between-sources variabilities. This paper reports on the first ENFSI evaluation campaign through a fake case, organized by the Netherlands Forensic Institute (NFI), as an example, where an automatic method using the Gaussian mixture models (GMMs) and the B
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A Machine Learning Approach to Off-Line Signature Verification Using Bayesian Inferenceble signatures for enrollment is small. On the NISDCC dataset, when enrolling 4 genuine signatures, the new method yielded a 12.1% average error rate, a significant improvement over a previously described Bayesian method.
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Zeno J. M. H. Geradts,Katrin Y. Franke,Cor J. Veen
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Statistical Evaluation of Biometric Evidence in Forensic Automatic Speaker Recognition(trace). This paper aims at presenting forensic automatic speaker recognition (FASR) methods that provide a coherent way of quantifying and presenting recorded voice as biometric evidence. In such methods, the biometric evidence consists of the quantified degree of similarity between speaker-depende
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Forensic Authorship Attribution Using Compression Distances to Prototypesages. These types of messages can easily be adjusted, such that meta data referring to names and addresses is at least unreliable. In this paper, we propose a method to identify authors of short informal messages solely based on the text content. The method uses compression distances between texts a
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