USING ARTIFICIAL INTELLIGENCE IN ASSESSING THE QUALITY OF STONES AND JEWELRY DESIGN
| dc.contributor.author | Edgar Bergamalyan | |
| dc.date.accessioned | 2025-12-28T10:50:26Z | |
| dc.date.issued | 2025-12-11 | |
| dc.description.abstract | This article briefly examines modern approaches to applying artificial intelligence (AI) methods to automated quality assessment of precious and ornamental stones (identification, origin determination, treatment detection, and 4C grading), as well as the potential of generative and auxiliary AI tools in jewelry design. Key algorithmic approaches (computer vision, convolutional neural networks, multimodal architectures, and spectral data processing methods) are discussed, along with case studies and commercial solutions, as well as issues of validation, standardization, and ethics. A review of key literature and practical results is provided. | |
| dc.format | application/pdf | |
| dc.identifier.uri | https://usajournals.org/index.php/2/article/view/1568 | |
| dc.identifier.uri | https://asianeducationindex.com/handle/123456789/4374 | |
| dc.language.iso | eng | |
| dc.publisher | Modern American Journals | |
| dc.relation | https://usajournals.org/index.php/2/article/view/1568/1646 | |
| dc.rights | https://creativecommons.org/licenses/by/4.0 | |
| dc.source | Modern American Journal of Engineering, Technology, and Innovation; Vol. 1 No. 9 (2025); 49-53 | |
| dc.source | 3067-7939 | |
| dc.subject | Artificial intelligence, stone quality assessment, machine learning, computer vision, gemology , generative design, jewelry, spectroscopic analysis | |
| dc.title | USING ARTIFICIAL INTELLIGENCE IN ASSESSING THE QUALITY OF STONES AND JEWELRY DESIGN | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
| dc.type | Peer-reviewed Article |
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