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Automated Goldsmith's Mark Retrieval in Silverware

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

For art historians, goldsmith marks play a critical role in the identification and dating of artifacts. In practice, experts must manually compare a query mark against hundreds of documented examples, a process that is both tedious and highly dependent on specialist knowledge. To address this, we present an AI-assisted retrieval pipeline that combines mark localization with metric-learning fine-tuning across three backbone architectures: an ImageNet-pretrained ResNet-50, a supervised ViT-S/16, and a self-supervised DINOv2 ViT-S/14. We conduct a systematic evaluation of cropping strategies, whe

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Evidence & attribution

First collected: 2026-09-19T20:28:14.107Z. This is not the publication date.