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YOLOv7-Large achieves 90.4% mAP50 for ancient coin character recognition

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a deep learning approach using YOLO variants for character recognition on ancient Roman Republican coins. They created a new dataset of 5,654 coin images with 38,808 annotations for 21 character labels. YOLOv7-Large demonstrated the highest performance with an mAP50 of 90.4%, outperforming other YOLO versions. AI

IMPACT Demonstrates advanced object detection capabilities for specialized historical data analysis.

RANK_REASON Academic paper detailing a novel dataset and object detection approach for historical artifact analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

YOLOv7-Large achieves 90.4% mAP50 for ancient coin character recognition

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Academic paper detailing a novel dataset and object detection approach for historical artifact analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Hafeez Anwar ·

    Reading Legends on Ancient Coins: An Object Detection Approach for Character Recognition on a Novel Roman Republican Dataset

    arXiv:2607.25455v1 Announce Type: new Abstract: When it comes to the proper classification of ancient coins with respect to their time and issuer, the textual inscriptions on these coins, also known as legends, are of paramount importance. These legends consist of alphabets or ch…

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