Predicting suitability of finger marks using machine learning techniques and examiner annotations

Author:

Eldridge Heidi,De Donno Marco,Champod Christophe

Funder

University of Lausanne

RTI International

Publisher

Elsevier BV

Subject

Pathology and Forensic Medicine,Law

Reference19 articles.

1. Examining and expanding the friction ridge value decision;Eldridge;Forensic Sci. Int.,2020

2. A Critical Analysis and Study of the Ace-V Process (Ph.D.);Langenburg,2012

3. Improving the Understanding and the Reliability of the Concept of ‘Sufficiency’ in Friction Ridge Examination;Neumann,2013

4. Miami-Dade Research Study for the Reliability of the ACE-V Process: Accuracy & Precision in Latent Fingerprint Examinations;Pacheco,2014

5. Accuracy and reliability of forensic latent fingerprint decisions;Ulery;Proc. Natl. Acad. Sci. USA,2011

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fingermark quality assessment, a transversal study of subjective quality scales;Forensic Science International;2023-09

2. Examination of Friction Ridge Impressions;Encyclopedia of Forensic Sciences, Third Edition;2023

3. Toward better AFIS practice and process in the forensic fingerprint environment;Forensic Science International: Synergy;2023

4. Interpol review of fingermarks and other body impressions (2019 – 2022);Forensic Science International: Synergy;2023

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