Hieroglyph Recognition with Deep Metric Learning
Published:Dec 30, 2025 12:58
•1 min read
•ArXiv
Analysis
This paper presents a significant advancement in the field of digital humanities, specifically for Egyptology. The OCR-PT-CT project addresses the challenge of automatically recognizing and transcribing ancient Egyptian hieroglyphs, a crucial task for researchers. The use of Deep Metric Learning to overcome the limitations of class imbalance and improve accuracy, especially for underrepresented hieroglyphs, is a key contribution. The integration with existing datasets like MORTEXVAR further enhances the value of this work by facilitating research and data accessibility. The paper's focus on practical application and the development of a web tool makes it highly relevant to the Egyptological community.
Key Takeaways
- •The paper introduces a semi-automatic method for recognizing ancient Egyptian hieroglyphs.
- •It utilizes Deep Metric Learning to address class imbalance and improve accuracy.
- •The system integrates with existing datasets for enhanced research capabilities.
- •A web tool is developed for organizing and accessing the recognized hieroglyphs.
Reference
“The Deep Metric Learning approach achieves 97.70% accuracy and recognizes more hieroglyphs, demonstrating superior performance under class imbalance and adaptability.”