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Firearms and Toolmarks

Treatment of inconclusives in the AFTE range of conclusions

In the past decade, and in response to the recommendations set forth by the National Research Council Committee on Identifying the Needs of the Forensic Sciences Community (2009), scientists have
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Using Machine Learning Methods to Predict Similarity of Striations on Bullet Lands

Recent advances in microscopy have made it possible to collect 3D topographic data, enabling virtual comparisons based on the collected 3D data next to traditional comparison microscopy. Automatic matching algorithms
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CSAFE 2021 Field Update

CSAFE 2021 Field Update

The 2021 Field Update was held June 14, 2021, and served as the closing to the first year of CSAFE 2.0. CSAFE brought together researchers, forensic science partners and interested
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Treatment of Inconclusive Results in Error Rates of Firearm Studies

This CSAFE webinar was held on February 10, 2021. Presenters: Heike Hofmann Professor and Kingland Faculty Fellow, Iowa State University Susan VanderPlas Research Assistant Professor, University of Nebraska, Lincoln Alicia
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CSAFE 2020 All Hands Meeting

The 2020 All Hands Meeting was held May 12 and 13, 2020 and served as the closing to the last 5 years of CSAFE research and focused on kicking off
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Comparison of three similarity scores for bullet LEA matching

Recent advances in microscopy have made it possible to collect 3D topographic data, enabling more precise virtual comparisons based on the collected 3D data as a supplement to traditional comparison
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A Robust Approach to Automatically Locating Grooves in 3D Bullet Land Scans

Land engraved areas (LEAs) provide evidence to address the same source–different source problem in forensic firearms examination. Collecting 3D images of bullet LEAs requires capturing portions of the neighboring groove
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Pattern Evidence Research in CSAFE-An Update

CSAFE is a NIST Center of Excellence in Forensic Science. A large portion of CSAFE’s research portfolio is on what is known as pattern evidence, which encompasses any evidence that
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Reproducibility of Automated Bullet Matching Scores Using High-Resolution 3D LEA Scans

Development of automated bullet matching algorithms based on 3D scans of land engraved areas (LEAs) has become a prominent area of research in recent years. However, automated methods rely heavily
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Adapting the Chumbley Score to Match Striae on Land Engraved Areas (LEAs) of Bullets

The same‐source problem remains a major challenge in forensic toolmark and firearm examination. Here, we investigate the applicability of the Chumbley method (J Forensic Sci, 2018, 63, 849; J Forensic
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