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A novel dataset of North-Eastern Indian coins for machine learning-based classification
Ishtiak Al Mamoon1, Saddat Kabir1, Ariful Islam1
1Department of Computer Science and Engineering, International University of Business Agriculture and Technology, Dhaka, Bangladesh.
Data in Brief
|May 25, 2026
Summary
This study introduces a new dataset of 2147 Indian coin images from North-Eastern regions, aiding machine learning for historical coin classification. This resource supports numismatic research and understanding ancient Bengali kingdoms.
Area of Science:
- Numismatics
- Computer Science
- Archaeology
Background:
- Ancient and medieval handmade coins present classification challenges due to their historical significance and intricate designs.
- Machine learning (ML) offers potential for coin classification but requires structured datasets.
Purpose of the Study:
- To present a novel, comprehensive dataset of Indian coins from North-Eastern regions (Assam, Tripura, Koch Bihar, Jaintiapur).
- To facilitate advanced machine learning applications for classifying historical Indian coinage.
Main Methods:
- Compilation of 2147 high-quality images across 51 classes of rare Indian coins.
- Data sourced from verified private collections and auction houses with expert numismatic verification.
- Inclusion of coins dating from the early 9th century AD to 1947.
Main Results:
- A well-structured dataset of 51 classes and 2147 images of North-Eastern Indian coins.
- The dataset captures scarce coins with intricate designs, crucial for numismatic study.
- Verified authenticity using numismatic series, auction records, and private collections.
Conclusions:
- The dataset is a valuable resource for advancing coin classification methodologies.
- It is expected to significantly contribute to the archaeological research of ancient North-Eastern Indian history and culture.
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