2024/04/02 by Tyler Houser, Alan B. McMillan, Beidi Dong · 1 voice
Social Sciences · Engineering · #Crime Patterns and Interventions #Traffic and Road Safety #Gun Ownership and Violence Research
paper · pdf · doi:10.1057/s41284-024-00423-7
openalex publication_date 2024/04/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
Abstract Gun violence significantly threatens tens of thousands of people annually in the United States. This paper proposes a multidisciplinary approach to address this issue. Specifically, we bridge the gap between criminology and computer vision by exploring the applicability of firearm object detection algorithms to the criminal justice system. By situating firearm object detection algorithms in situational crime prevention, we outline how they could enhance the current use of closed-circuit television (CCTV) systems to mitigate gun violence. We elucidate our approach to training a firearm object detection algorithm and describe why its results are meaningful to scholars beyond the realm of computer vision. Lastly, we discuss limitations associated with object detection algorithms and why they are valuable to criminal justice practices.