Deep Learning-Enhanced Jewelry Material Jadeite Jade Quality Assessment

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Publicat a:JOM vol. 77, no. 1 (Jan 2025), p. 211
Autor principal: Meng, Liang
Altres autors: Effendi, Raja Ahmad Azmeer Raja Ahmad, Sun, Wei, Mo, Lili, Rahman, Ahmad Rizal Abdul, Hsu, Yu-lin, Barron, Deirdre
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Springer Nature B.V.
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100 1 |a Meng, Liang  |u Faculty of Design and Architecture, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia 
245 1 |a Deep Learning-Enhanced Jewelry Material Jadeite Jade Quality Assessment 
260 |b Springer Nature B.V.  |c Jan 2025 
513 |a Journal Article 
520 3 |a 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. 
651 4 |a United States--US 
651 4 |a China 
653 |a Deep learning 
653 |a Culture 
653 |a Artificial neural networks 
653 |a Jewelry 
653 |a Machine learning 
653 |a Research & development--R&D 
653 |a Quality assessment 
653 |a Artificial intelligence 
653 |a Computer vision 
653 |a Jewelry industry 
653 |a Neural networks 
653 |a Classification 
653 |a Image classification 
653 |a Design 
653 |a Computer aided design--CAD 
653 |a Algorithms 
653 |a Image quality 
653 |a Designers 
653 |a Screening 
700 1 |a Effendi, Raja Ahmad Azmeer Raja Ahmad  |u Faculty of Design and Architecture, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia 
700 1 |a Sun, Wei  |u Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia 
700 1 |a Mo, Lili  |u Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia, 43600 Bangi, Malaysia 
700 1 |a Rahman, Ahmad Rizal Abdul  |u Faculty of Design and Architecture, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia 
700 1 |a Hsu, Yu-lin 
700 1 |a Barron, Deirdre 
773 0 |t JOM  |g vol. 77, no. 1 (Jan 2025), p. 211 
786 0 |d ProQuest  |t Science Database 
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856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3159699230/fulltext/embedded/IZYTEZ3DIR4FRXA2?source=fedsrch 
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