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Evidence record 17143 · automatically gathered

Generative AI-enhanced synthetic X-ray augmentation with gradient-based selection for battery detection in WEEE

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

Record details

Published: 6 August 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Environment
Retrieved: 7 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (6 August 2026), “Generative AI-enhanced synthetic X-ray augmentation with gradient-based selection for battery detection in WEEE,” evidence record 17143, https://ethics.ai/record/17143 (originally published by Frontiers in Artificial Intelligence).

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