Transformers vs. CNNs: Who Reads Ancient Roman Coins Better?
Can AI read ancient coins?
Ancient Roman coins are tiny time capsules—but there are millions, and decoding their symbols is slow work. A new study by David Reid and Ognjen Arandjelovic tests whether modern AI can spot coin motifs (like emperors, gods, altars) more reliably.
The team compared classic convolutional neural networks (CNNs) with Vision Transformers (ViTs). Unlike CNNs, ViTs look at an image in “patches” and can also learn from unstructured text that accompanies coin images—auction notes, catalog blurbs, and more.
The result: ViTs outperformed the newly trained CNNs in accuracy when identifying these semantic elements, using fully automatic multi-modal learning (images + text).
Why it matters: faster, scalable identification can help researchers mine huge collections for historical insights—and help collectors verify what they’re buying or selling.
Transformers don’t just label coins; they help surface stories stamped in metal.
Read the preprint: https://arxiv.org/abs/2601.09433v1
Paper: https://arxiv.org/abs/2601.09433v1
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