Deep Learning-Enhanced Jewelry Material Jadeite Jade Quality Assessment

IF 2.1 4区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY
JOM Pub Date : 2024-10-30 DOI:10.1007/s11837-024-06930-7
Liang Meng, Raja Ahmad Azmeer Raja Ahmad Effendi, Wei Sun, Lili Mo, Ahmad Rizal Abdul Rahman, Yu-Lin Hsu, Deirdre Barron
{"title":"Deep Learning-Enhanced Jewelry Material Jadeite Jade Quality Assessment","authors":"Liang Meng,&nbsp;Raja Ahmad Azmeer Raja Ahmad Effendi,&nbsp;Wei Sun,&nbsp;Lili Mo,&nbsp;Ahmad Rizal Abdul Rahman,&nbsp;Yu-Lin Hsu,&nbsp;Deirdre Barron","doi":"10.1007/s11837-024-06930-7","DOIUrl":null,"url":null,"abstract":"<div><p>Jadeite jade, renowned for its unique texture and cultural significance, stands as the epitome of jade varieties, embodying the latest evolution of China's jade culture. This research endeavors to establish an AI model for precisely screening jadeite quality, employing deep learning techniques to revolutionize jadeite design and detection. The objective is to provide jewelry companies, designers, and customers with an unbiased means of grading and evaluating jadeite quality. We have meticulously curated a database of jadeite images, applied preprocessing techniques, and have harnessed convolutional neural networks (CNN) for feature extraction. The outcomes were promising, with the model achieving notable performance indicators: an accuracy rate of approximately 84.75%, a recall rate of about 84.94%, and an F1 score of roughly 73.76% in jade image classification tasks. These results underscore the model's effectiveness in the assessment of jadeite quality. Incorporating computer-aided technology into jadeite screening foreshadows a transformative era where artificial intelligence seamlessly integrates with traditional jade carving design, signifying a pivotal shift in the industry's landscape.</p></div>","PeriodicalId":605,"journal":{"name":"JOM","volume":"77 1","pages":"211 - 224"},"PeriodicalIF":2.1000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOM","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1007/s11837-024-06930-7","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Jadeite jade, renowned for its unique texture and cultural significance, stands as the epitome of jade varieties, embodying the latest evolution of China's jade culture. This research endeavors to establish an AI model for precisely screening jadeite quality, employing deep learning techniques to revolutionize jadeite design and detection. The objective is to provide jewelry companies, designers, and customers with an unbiased means of grading and evaluating jadeite quality. We have meticulously curated a database of jadeite images, applied preprocessing techniques, and have harnessed convolutional neural networks (CNN) for feature extraction. The outcomes were promising, with the model achieving notable performance indicators: an accuracy rate of approximately 84.75%, a recall rate of about 84.94%, and an F1 score of roughly 73.76% in jade image classification tasks. These results underscore the model's effectiveness in the assessment of jadeite quality. Incorporating computer-aided technology into jadeite screening foreshadows a transformative era where artificial intelligence seamlessly integrates with traditional jade carving design, signifying a pivotal shift in the industry's landscape.

求助全文
约1分钟内获得全文 求助全文
来源期刊
JOM
JOM 工程技术-材料科学:综合
CiteScore
4.50
自引率
3.80%
发文量
540
审稿时长
2.8 months
期刊介绍: JOM is a technical journal devoted to exploring the many aspects of materials science and engineering. JOM reports scholarly work that explores the state-of-the-art processing, fabrication, design, and application of metals, ceramics, plastics, composites, and other materials. In pursuing this goal, JOM strives to balance the interests of the laboratory and the marketplace by reporting academic, industrial, and government-sponsored work from around the world.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信