@article{ref1,
title="Human and machine similarity judgments in forensic firearm comparisons",
journal="Forensic science international : synergy",
year="2022",
author="Cuellar, Maria and Gonzalez, Cleotilde and Dror, Itiel E.",
volume="5",
number="",
pages="e100283-e100283",
abstract="It is unclear whether humans assess similarity differently than automated algorithms in firearms comparisons. Human participants (untrained in firearm examination) were asked to assess the similarity of pairs of images (from 0 to 100). A sample of 40 pairs of cartridge casing 2D-images was used. The images were divided into 4 groups according to their similarity as determined by an algorithm. Humans were able to distinguish between matches and non-matches (both when shown the 2 middle groups, as well as when shown all 4 groups). Thus, humans are able to make high-quality similarity judgments in firearm comparisons based on two images. The humans' similarity scores were superior to the algorithms' scores at distinguishing matches and non-matches, but inferior in assessing similarity within groups. This suggests that humans do not have the same group thresholds as the algorithm, and that a hybrid human-machine approach could provide better identification results than humans or algorithms alone.<p /> <p>Language: en</p>",
language="en",
issn="2589-871X",
doi="10.1016/j.fsisyn.2022.100283",
url="http://dx.doi.org/10.1016/j.fsisyn.2022.100283"
}