Gaborini Lorenzo, Biedermann Alex, Taroni Franco
University of Lausanne, School of Criminal Justice, Lausanne, Switzerland.
University of Lausanne, School of Criminal Justice, Lausanne, Switzerland.
Sci Justice. 2017 May;57(3):209-220. doi: 10.1016/j.scijus.2017.01.004. Epub 2017 Jan 31.
In this work, we propose the construction of a evaluative framework for supporting experts in questioned signature examinations. Through the use of Bayesian networks, we envision to quantify the probative value of well defined measurements performed on questioned signatures, in a way that is both formalised and part of a coherent approach to evaluation. At the current stage, our project is explorative, focusing on the broad range of aspects that relate to comparative signature examinations. The goal is to identify writing features which are both highly discriminant, and easy for forensic examiners to detect. We also seek for a balance between case-specific features and characteristics which can be measured in the vast majority of signatures. Care is also taken at preserving the interpretability at every step of the reasoning process. This paves the way for future work, which will aim at merging the different contributions to a single probabilistic measure of strength of evidence using Bayesian networks.
在这项工作中,我们提议构建一个评估框架,以支持专家进行有疑问签名检验。通过使用贝叶斯网络,我们设想以一种形式化且是连贯评估方法一部分的方式,量化对有疑问签名进行的明确测量的证明力。在当前阶段,我们的项目具有探索性,专注于与比较签名检验相关的广泛方面。目标是识别出具有高度区分性且法医检验人员易于检测的书写特征。我们还寻求在特定案例特征与绝大多数签名中可测量的特征之间取得平衡。在推理过程的每一步都注意保持可解释性。这为未来的工作铺平了道路,未来工作旨在使用贝叶斯网络将不同贡献合并为单一的证据强度概率度量。