A novel dataset of Gupta archer type coins for machine learning-based classification
In the field of numismatics, classifying ancient coins, especially those that have diverse information and cultural heritage is a difficult task. Machine learning algorithms have recently made remarkable advancements in these types of tasks. However, these algorithms largely rely on relevant datasets. This article presents a novel dataset of ancient Gupta archer-type coin images, collected from verified private collections and three popular auction houses with their permission. The images exclusively comprise authentic specimens of ancient Gupta archer-type coins. We aim to establish a reliable resource that adheres to the highest standards of numismatic research. These coins, characterized by their distinctive archer motifs, present a significant challenge in terms of identification due to their scarcity and the intricate nature of their design. To address this, we meticulously curated a dataset by annotating each coin through a combination of visual examination and leveraging insights from numismatic literatures. These coins inherit ancient Indian archaeological insights, and studying these coins could provide insights into ancient Indian archaeology.
Authors
- Rubyat Tasnuva Hasan (ORCID: https://orcid.org/0000-0001-8803-6857)
- Pranto Dev
- Muhammad E. H. Chowdhury (ORCID: https://orcid.org/0000-0003-0744-8206)
- Zakaria Shams Siam (ORCID: https://orcid.org/0000-0002-7502-2285)
- Ishtiak Al Mamoon
- Abdul Akhir Al Galib
- Theophil Dango
- Kalin Chakma
Institutions
- Albany State University (US)
- University at Albany, State University of New York (US)
- Biomedical Research Foundation (BD)
- BRAC University (BD)
- Qatar University (QA)
Publication Details
- Journal
- Data in Brief
- Published
- 2024-09-17
- DOI
- https://doi.org/10.1016/j.dib.2024.110934
- Citations
- 3
- Primary Topic
- Currency Recognition and Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.75
Funders
- Qatar National Library