{
  "id": 13188,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1867175",
  "title": "An explainable end-to-end computer vision pipeline for detection, segmentation, and reconstruction of occluded weapons in forensic imagery",
  "summary": "IntroductionImages from crime scenes often show partially concealed weapons due to obstructions such as hands and clothing, as well as surveillance camera limitations, which affect the efficacy of traditional detection methods. This work proposes an explainable forensic pipeline for occluded weapons detection, segmentation, and reconstruction.MethodsThe proposed framework integrates RT-DETR-L, a transformer-based weapon detection model; MobileSAM for zero-shot segmentation of visible weapon regi",
  "authors": "Vaibhav Rohella",
  "category": "research",
  "topics": "privacy-surveillance,military-security,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-23T00:00:00.000Z",
  "fetched_at": "2026-07-25T05:10:48.796Z",
  "source_slug": "x-frontiers-in-artificial-intelligence",
  "source_name": "Frontiers in Artificial Intelligence",
  "source_homepage": "https://www.frontiersin.org/journals/artificial-intelligence",
  "ethics_ai_record_url": "https://ethics.ai/record/13188",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1867175",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}