Deep learning-enhanced jewelry material jadeite jade quality assessment - Meng, Liang; Raja Ahmad Effendi, Raja Ahmad Azmeer; Sun, Wei; Mo, Lili; Abdul Rahman, Ahmad Rizal; Hsu, Yu-Lin; Barron, Deirdre (Springer, 2024)
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 transforma- tive era where artificial intelligence seamlessly integrates with traditional jade carving design, signifying a pivotal shift in the industry’s landscape.