
Article History
Received: 24 June 2024
Accepted: 27 June 2024
Published: 18 July 2024
MEMBER:
Volume 2, Issue 1, 2nd Quarter 2024, pp. 29 – 39
Utilization of Convolutional Neural Networks in Coin Grading for BSP Series One Peso Coins
Author:
John Dustin D. Santos, Michael B. Dela Fuente
Abstract:
Identifying the grade of the coin is one of the methods used in numismatics to get the condition and collector’s
values of a coin. Coin grading is subjective and sensitive in nature in which at least three (3) numismatists or
coin graders or experts are needed to have a persuasive result or coin grade. This paper aimed to develop a
tool that will give an accurate and objective grade of a coin. The main objective of this paper is to check whether
a developed tool can accurately grade a coin based on its image only. This study used a Convolutional Neural
Network (CNN) as image analysis algorithm for the developed tool and three hundred (300) BSP Series one
peso coin images for each of the five-coin grades were also generated as dataset for the tool to perform its
function. Major results produced a more accurate tool that gave a specific grade of a coin. A group of
numismatists or coin graders or experts evaluated the developed coin grading tool in which it acquired very
satisfactory results. Convolutional neural network is proven to be effective in accurately and objectively grading
coin images and can be a great help for numismatist in appraising coins. This can be improved by considering
variety of coins for grading.
Keywords: BSP Coin Series, Coin Grading, Convolutional Neural Network, Image Analysis, Numismatics
Cited by
Expert system for coin condition assessment using interval type-2 fuzzy sets
Artem Kharchenko, Natalia Pasichnyk & Renat Rizhniak
Published online: 06 April 2026
2026 IEEE 18th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (IEEE)
Crossref
Enabling automatic coin grading through late-fusion of vision–language and hierarchical transformers
Melaku N. Getahun & Andrey Somov
Published online: 04 June 2026
IEEE Transactions on Instrumentation and Measurement (IEEE)
Crossref
Automatic coin grading: model based on siamese neural network with EfficientNet encoders
Makar Korchagin, Melaku N. Getahun, Abdelrahman Metwally, Anna Baldycheva & Andrey Somov
Published online: 21 October 2025
2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (IEEE)
Crossref
Indexed:


Licensed by:

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b. Select the Journal
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e. Peer Review Process
f. Manuscript Revision
g. Editing Services
h. Final Manuscript Submission
i. Acknowledgement to Publish
j. Copyright Matters
k. Inhouse Publication

Article History
Received: 24 June 2024
Accepted: 27 June 2024
Published: 18 July 2024
Volume 2, Issue 1, 2nd Quarter 2024, pp. 29 – 39
Utilization of Convolutional Neural Networks in Coin Grading for BSP Series One Peso Coins
Author:
John Dustin D. Santos, Michael B. Dela Fuente
Abstract:
Identifying the grade of the coin is one of the methods used in numismatics to get the condition and collector’s
values of a coin. Coin grading is subjective and sensitive in nature in which at least three (3) numismatists or
coin graders or experts are needed to have a persuasive result or coin grade. This paper aimed to develop a
tool that will give an accurate and objective grade of a coin. The main objective of this paper is to check whether
a developed tool can accurately grade a coin based on its image only. This study used a Convolutional Neural
Network (CNN) as image analysis algorithm for the developed tool and three hundred (300) BSP Series one
peso coin images for each of the five-coin grades were also generated as dataset for the tool to perform its
function. Major results produced a more accurate tool that gave a specific grade of a coin. A group of
numismatists or coin graders or experts evaluated the developed coin grading tool in which it acquired very
satisfactory results. Convolutional neural network is proven to be effective in accurately and objectively grading
coin images and can be a great help for numismatist in appraising coins. This can be improved by considering
variety of coins for grading.
Keywords: BSP Coin Series, Coin Grading, Convolutional Neural Network, Image Analysis, Numismatics
Cited by
Expert system for coin condition assessment using interval type-2 fuzzy sets
Artem Kharchenko, Natalia Pasichnyk & Renat Rizhniak
Published online: 06 April 2026
2026 IEEE 18th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (IEEE)
Crossref
Enabling automatic coin grading through late-fusion of vision–language and hierarchical transformers
Melaku N. Getahun & Andrey Somov
Published online: 04 June 2026
IEEE Transactions on Instrumentation and Measurement (IEEE)
Crossref
Automatic coin grading: model based on siamese neural network with EfficientNet encoders
Makar Korchagin, Melaku N. Getahun, Abdelrahman Metwally, Anna Baldycheva & Andrey Somov
Published online: 21 October 2025
2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (IEEE)
Crossref
Indexed:


Licensed by:

Submit Articles:
A. CURATED/INHOUSE JOURNALS
1. Journal Description
2. Select Journal
a. Declaration of Originality
b. Select the Journal
c. Paper Formatting
d. Initial Manuscript Submission
e. Peer Review Process
f. Manuscript Revision
g. Editing Services
h. Final Manuscript Submission
i. Acknowledgement to Publish
j. Copyright Matters
k. Inhouse Publication

Article History
Received: 24 June 2024
Accepted: 27 June 2024
Published: 18 July 2024
Volume 2, Issue 1, 2nd Quarter 2024, pp. 29 – 39
Utilization of Convolutional Neural Networks in Coin Grading for BSP Series One Peso Coins
Author:
John Dustin D. Santos, Michael B. Dela Fuente
Abstract:
Identifying the grade of the coin is one of the methods used in numismatics to get the condition and collector’s
values of a coin. Coin grading is subjective and sensitive in nature in which at least three (3) numismatists or
coin graders or experts are needed to have a persuasive result or coin grade. This paper aimed to develop a
tool that will give an accurate and objective grade of a coin. The main objective of this paper is to check whether
a developed tool can accurately grade a coin based on its image only. This study used a Convolutional Neural
Network (CNN) as image analysis algorithm for the developed tool and three hundred (300) BSP Series one
peso coin images for each of the five-coin grades were also generated as dataset for the tool to perform its
function. Major results produced a more accurate tool that gave a specific grade of a coin. A group of
numismatists or coin graders or experts evaluated the developed coin grading tool in which it acquired very
satisfactory results. Convolutional neural network is proven to be effective in accurately and objectively grading
coin images and can be a great help for numismatist in appraising coins. This can be improved by considering
variety of coins for grading.
Keywords: BSP Coin Series, Coin Grading, Convolutional Neural Network, Image Analysis, Numismatics
Cited by
Expert system for coin condition assessment using interval type-2 fuzzy sets
Artem Kharchenko, Natalia Pasichnyk & Renat Rizhniak
Published online: 06 April 2026
2026 IEEE 18th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (IEEE)
Crossref
Enabling automatic coin grading through late-fusion of vision–language and hierarchical transformers
Melaku N. Getahun & Andrey Somov
Published online: 04 June 2026
IEEE Transactions on Instrumentation and Measurement (IEEE)
Crossref
Automatic coin grading: model based on siamese neural network with EfficientNet encoders
Makar Korchagin, Melaku N. Getahun, Abdelrahman Metwally, Anna Baldycheva & Andrey Somov
Published online: 21 October 2025
2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (IEEE)
Crossref
Indexed:


Licensed by:


