USING ARTIFICIAL INTELLIGENCE IN ASSESSING THE QUALITY OF STONES AND JEWELRY DESIGN

dc.contributor.authorEdgar Bergamalyan
dc.date.accessioned2025-12-28T10:50:26Z
dc.date.issued2025-12-11
dc.description.abstractThis 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.formatapplication/pdf
dc.identifier.urihttps://usajournals.org/index.php/2/article/view/1568
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/4374
dc.language.isoeng
dc.publisherModern American Journals
dc.relationhttps://usajournals.org/index.php/2/article/view/1568/1646
dc.rightshttps://creativecommons.org/licenses/by/4.0
dc.sourceModern American Journal of Engineering, Technology, and Innovation; Vol. 1 No. 9 (2025); 49-53
dc.source3067-7939
dc.subjectArtificial intelligence, stone quality assessment, machine learning, computer vision, gemology , generative design, jewelry, spectroscopic analysis
dc.titleUSING ARTIFICIAL INTELLIGENCE IN ASSESSING THE QUALITY OF STONES AND JEWELRY DESIGN
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

item.page.files

item.page.filesection.original.bundle

pagination.showing.labelpagination.showing.detail
loading.default
thumbnail.default.alt
item.page.filesection.name
bergamalyan_2025_using_artificial_intelligence_in_assessi.pdf
item.page.filesection.size
320.46 KB
item.page.filesection.format
Adobe Portable Document Format