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Handwriting

Score-based Likelihood Ratios Using Stylometric Text Embeddings

We consider the problem setting in which we have two sets of texts in digital form and would like to quantify our beliefs that the two sets of texts were
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Challenges in Modeling, Interpreting, and Drawing Conclusions from Images as Forensic Evidence

When a crime is committed, law enforcement directs crime scene experts to obtain evidence that may be pertinent to identifying the perpetrator(s). Much of this evidence comes in the form
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Quantifying Bayes Factors for Forensic Handwriting Evidence

This presentation is from the 76th Annual Conference of the American Academy of Forensic Sciences (AAFS), Denver, Colorado, February 19-24, 2024.
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Quantifying Writer Variance Through Rainbow Triangle Graph Decomposition

This presentation is from the 76th Annual Conference of the American Academy of Forensic Sciences (AAFS), Denver, Colorado, February 19-24, 2024
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A deep learning approach for the comparison of handwritten documents using latent feature vectors

Forensic questioned document examiners still largely rely on visual assessments and expert judgment to determine the provenance of a handwritten document. Here, we propose a novel approach to objectively compare
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A statistical approach to aid examiners in the forensic analysis of handwriting

We develop a statistical approach to model handwriting that accommodates all styles of writing (cursive, print, connected print). The goal is to compute a posterior probability of writership of a
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CSAFE Project Update & ASCLD FRC Collaboration

This presentation highlighted CSAFE’s collaboration with the ASCLD FRC Collaboration Hub.
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Twin Convolutional Neural Networks to Classify Writers Using Handwriting Data

Identifying the source of handwriting is an important application in the field of forensic science that addresses questioned document evidence found in criminal cases and civil litigation. It is difficult,
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Quantifying Bayes Factors for Forensic Handwriting Evidence

Questioned Document Examiners (QDEs) are tasked with analyzing handwriting evidence to make source (or writership) determinations. The Center for Statistics and Applications of Forensic Evidence (CSAFE) has previously developed computational
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Quantifying Writer Variance Through Rainbow Triangle Graph Decomposition of the Common Word “the”

Handwriting comparative analysis is based on the principle that no two individuals can produce the same writing and that an individual cannot exactly reproduce his/her handwriting. This project aims to
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