{
  "id": 17143,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1881543",
  "title": "Generative AI-enhanced synthetic X-ray augmentation with gradient-based selection for battery detection in WEEE",
  "summary": "Automated detection of batteries in Waste Electrical and Electronic Equipment (WEEE) using X-ray imaging is critical for safe recycling, yet collecting large annotated real-world datasets remains prohibitively expensive and hazardous. This paper proposes a three-stage synthetic data pipeline to improve battery detection under limited labeled data conditions. First, dual-energy X-ray images are generated using physics-based ray-casting in Blender with automatic pixel-level annotation. Second, the",
  "authors": "Farhan Mahmood",
  "category": "research",
  "topics": "environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-06T00:00:00.000Z",
  "fetched_at": "2026-08-07T05:10:58.501Z",
  "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/17143",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1881543",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}