Explainable AI-Driven Framework for Gemstone Quality Assessment

Gemstones play a significant role in the global economy as a key export product. This paper presents a comprehensive approach to optimizing gemstone damage identification and grading through an integrated mobile application. Utilizing real-time computer vision-based techniques and explainable AI (XAI), the system addresses the critical challenges of subjective grading and inconsistent assessments. The application enhances accuracy in gemstone grading by employing advanced deep learning algorithms, particularly convolutional neural networks (CNNs), and provides explainable insights into damage detection processes. Findings demonstrate that the model significantly reduces human error and increases transparency, offering gemologists, traders, and enthusiast's reliable decision-making support. This approach enhances operational efficiency and promotes standardization across the gemstone industry, making it a valuable tool for global market stakeholders.