activity
20102025
most citedConstruction and evaluation of classifiers for forensic document analysis

18 citations · 24 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2025

Deep Learning for Forensic Identification of Source

Cole Patten, Christopher Saunders, Michael Puthawala

We used contrastive neural networks to learn useful similarity scores between the 144 cartridge casings in the NBIDE dataset, under the common-but-unknown source paradigm. The comm…

math.ST2019★ 1 cited

Reconciling the Bayes Factor and Likelihood Ratio for Two Non-Nested Model Selection Problems

Danica M. Ommen, Christopher P. Saunders

In statistics, there are a variety of methods for performing model selection that all stem from slightly different paradigms of statistical inference. The reasons for choosing one…

stat.ME2018★ 3 cited

Two-stage approach for the inference of the source of high-dimension and complex chemical data in forensic science

Madeline Ausdemore, Cedric Neumann, Christopher Saunders +2

Forensic scientists are often criticised for the lack of quantitative support for the conclusions of their examinations. While scholars advocate for the use of a Bayes factor to qu…

stat.ME2018★ 1 cited

Quantification of the weight of fingerprint evidence using a ROC-based Approximate Bayesian Computation algorithm for model selection

J. H. Hendricks, C. Neumann, C. P. Saunders

For more than a century, fingerprints have been used with considerable success to identify criminals or verify the identity of individuals. The categorical conclusion scheme used b…

stat.AP2015★ 1 cited

A Note on the Specific Source Identification Problem in Forensic Science in the Presence of Uncertainty about the Background Population

Danica M. Ommen, Christopher P. Saunders, Cedric Neumann

A goal in the forensic interpretation of scientific evidence is to make an inference about the source of a trace of unknown origin. The evidence is composed of the following three…

stat.AP2010★ 18 cited

Construction and evaluation of classifiers for forensic document analysis

Christopher P. Saunders, Linda J. Davis, Andrea C. Lamas +2

In this study we illustrate a statistical approach to questioned document examination. Specifically, we consider the construction of three classifiers that predict the writer of a…